Chen Weng
@chenweng1991
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Postdoc in Sankaran lab and Weissman lab @bloodgenes & @JswLab || Single-cell genomics/Cell-fate commitment/Gene regulation/
Cambridge, MA
Joined February 2012
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Pinned Tweet
Very delighted to share our work Deciphering cell states and genealogies of human hematopoiesis online today in
@Nature
(Accelerated Preview version). It is a really great collaboration of Weissman lab
@JswLab
and Sankaran lab
@bloodgenes
🧵(1/n)
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A recent commentary in bioRxiv discussed data analysis for our mtDNA-based lineage tracing technology ReDeeM. We welcome the points raised and are happy to address these concerns. We believe this will foster constructive dialogue (1/n)
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Delighted to share our work studying the molecular control for the directed β cell differentiation process
@NatMetabolism
Great collaboration with Jiajia Xi
@FulaiJin
lab and Yan Li lab
@CWRUSOM
.
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Delighted to share the last piece of my graduate school work that dissects disease-associated single-cell heterogeneity and continuum through multiomics
@NatureComms
.
#SingleCell
#Multiomics
#diabetes
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As a trainee, I appreciate rigorous scientific discussions and am always seeking to improve my scientific work. I believe we all share the common goal of promoting robust science and creating a healthy scientific environment where everyone enjoys science.(18/n)
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Massively parallel base editing to map variant effects in human hematopoiesis. Incredibly powerful to study variant-to-function at scale with single-nucleotide resolution in primary human cells. Amazing work!
@jmartinrufino
@bloodgenes
Thrilled to share my PhD work in
@CellCellPress
! Massively parallel base editing to map variant effects in human hematopoiesis. We developed screens on blood stem cells to understand disease and develop treatments at single-nucleotide resolution.1/n
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I'm truly grateful for the rigorous, supportive, and constructive environment around me. Special thanks to my co-mentors
@bloodgenes
@JswLab
for their guidance, and heartfelt appreciation to my colleagues and family for their invaluable support!
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First, mitigating artifacts is at the core of ReDeeM design. It uses overlapping paired-end sequencing and double-stranded UMIs (similar to duplex-seq) to not only remove PCR and sequencing errors, but also reduce artifacts in one strand of the initial molecules. (5/n)
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@alexa_schnell
@KatieEYost
@LukeKoblan
@jmartinrufino
, many thanks to reviewers for their helpful suggestions, and also thanks for the very inspiring pioneering work on mitochondrial lineage tracing from
@LeifLudwig
@CalebLareau
, and colleagues. (end)
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Excited to be presenting our work reconstructing single cell developmental tree for human pancreatic beta cell differentiation at
#ashg19
9am in level 3, ballroom C!
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How to track detailed cell fate/behaviors over time in humans in vivo? Technologies that can simultaneously provide single-cell state and genealogical information from natural cellular barcodes (somatic mutations) would, in principle, provide a solution. (2/n)
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By way of background, we had described the single-cell Regulatory multi-omics with Deep Mitochondrial mutation profiling (ReDeeM) approach in a
@Nature
paper earlier this year: (2/n)
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Our work on disease associated single-cell trajectory in pancreatic beta cell combined with genome-wide CRISPR screen is out
@CellReports
! Great collaboration with Zhou. Check our RePACT for disease trajectory analysis
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We acknowledge the limitations of ReDeeM and mtDNA lineage tracing. Our goal is not to build perfect trees with these mutations alone, but explore what is possible with improved sensitivity to gain deeper insights into cell-cell relationships and uncover valuable biology. (16/n)
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We show that the cells remain well connected with additional filtering, yielding consistent results with CRISPR-based lineage tracing and maintaining important lineage substructure including nearest neighborhoods. (14/n)
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How does HSC genealogical structure change in aging? ReDeeM reveals reduced hematopoietic stem cell clonal diversity in aging at single-cell level, marked by multiple distinct clonal expansions, each with its own skewed cell type distribution. (10/n)
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The “mutation in one molecule per cell” in question is rigorously controlled. To be included in ReDeeM: (1) Each molecule is supported by on average 4.8 PE-reads (9.6 reads). (2) it must be supported by at least two molecules in one cell and detected in multiple cells. (6/n)
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We appreciate the commentary highlighting edge-accumulated mutations. While they affect only a small proportion, we recognize the value of managing them and we offer an additional filtering option in ReDeeM-R. (11/n)
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Our additional filtering with minimal edge trimming (4-5 bp) effectively removes position biases, resulting in a mutational signature indistinguishable from ground truth for one-molecule mutations, with an estimated accuracy of ≥95% based on transversion proportion. (12/n)
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The commentary argues that one-molecule mutations are enriched on edges and suggests removing all of them. However, in our hematopoietic stem cell (HSC) study, 75% of these mutations are not on edges. (9/n)
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We are excited to enable others to use ReDeeM and look forward to further developments of these approaches. Please stay tuned for more advances in this area that will be forthcoming. (17/n)
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💡We present an in-depth analysis showing that the mutations in question are strongly supported and informative. Edge mutations affect a small proportion of molecules, and we've added filtering options to further reinforce the robustness of ReDeeM. See below (4/n)
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The commentary argues that mutations detected in 1 molecule per cell are poorly supported and enriched on edges of mtDNA molecules. It is then argued that these mutations resemble artifacts and should be all removed. (3/n)
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The above evidence suggests that the proposed removal of all 'mutations in one molecule per cell' would lead to massive elimination of bona fide and informative mutations. (8/n)
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We surveyed the relationships between HSC clones and their molecular states preference, revealing a partially heritable and relatively stable state-preference for approximately one third of HSC clones. (8/n)
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The “mutation in one molecule per cell” is further supported by various lines of evidence. (1) show strong mutational signature (2) significantly deviate from background error. (3) are supported by CRISPR-based lineage tracing. (4) Provide valuable biological insights. (7/n)
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I’m immensely grateful to my amazing joint mentors
@JswLab
@bloodgenes
and all collaborators and colleagues, in particular
@vangalenlab
Sahand Hormoz lab,
@fulong_yu
@dianyang1117
@michaelpoeschla
@la_liggett
@MattG_Jones
@Xiaojie_Qiu
@LWahlster
Alexis Caulier
@jeff_hussmann
…
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Our additional filtering only slightly reduces the total number of unique mutations, with over 10-fold more variants than prior methods. Mutations detected exclusively by ReDeeM are validated by strong mutational signatures. (13/n)
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For a systemic benchmark, we utilized a mouse model with engineered CRISPR-based evolving barcodes. We jointly detect both CRISPR-based tracers and the natural mtDNA somatic mutations by ReDeeM, revealing significant consistency at single-cell and subclonal levels. (6/n)
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We show the topology of the tree remains informative with additional filtering. We observe consistent polyclonal structures in young donors and significantly altered clonality in aged donors after applying the additional filtering strategies. (15/n)
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Open full-text link to this work is available here:
Delighted to share our work studying the molecular control for the directed β cell differentiation process
@NatMetabolism
Great collaboration with Jiajia Xi
@FulaiJin
lab and Yan Li lab
@CWRUSOM
.
3
7
50
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0
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Yang lab hiring
@Columbia
State-of-art tracking and recording technologies in understanding tumor evolution and cancer plasticity
Excited to announce the Yang lab officially opens at
@Columbia
University. We are interested in developing innovative single cell recording technologies to study tumor evolution and cancer plasticity. We are hiring motivated postdocs & students, please RT
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However, detecting natural somatic mutations at the single-cell level remains challenging, yet its sensitivity is key in determining the resolution of the lineage tracing, i.e., from clonal to subclonal and genealogical levels. (3/n)
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Indeed, excessive edge mutations impact only a small proportion of molecules overall. HSCs are the least impacted, with 4.3% to 7.6% excess edge mutations. We also show these are distinct from previously reported artifacts and discuss potential sources. (10/n)
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We reasoned that ReDeeM could tackle challenging open problems in hematopoietic stem cells (HSCs) in humans in vivo. To do that, we firstly enriched and refined HSC population and charted the HSC genealogical architecture and cell state heterogeneity (7/n)
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Impressive work to demonstrate purifying selections of mitochondrial pathogenic mutations in cell-state specific manner! Congrats
@CalebLareau
@LeifLudwig
and colleagues!
Out today in
@NatureGenet
, our work utilizing single-cell multi-omics to define specific immune cell subsets that experience purifying selection against pathogenic mitochondrial DNA. Check out a thread about this work below: 1/22
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So excited for you, my friend! Xiaojie Qiu is starting his own lab at Stanford Dec 16th! He is working on really cool stuff in spatial-temporal modeling of single cell genomics in development. His lab is recruiting! Please reach out to him if you are interested!
I am profoundly humbled and excited to officially announce that I will start my independent lab at Stanford this Dec. 16th. Growing up as the son of farmers in a remote village in China and facing the loss of my father at an age of 10, this journey has been anything but easy.
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We developed ReDeeM, a single-cell multiomics platform featuring ultra-sensitive mitochondrial DNA (mtDNA) variant calling and joint RNA+ATAC profiling. With significantly improved natural barcode detectability, ReDeeM enables fine-scale subclonal and phylogenetic analyses. (4/n)
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We linked the differentiated progenies to HSC clonal groups, allowing for the direct measurement of HSC behaviors in humans in vivo. We observed sustainable HSC output activity and differentiation biases, likely due to epigenetic priming. (9/n)
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We believe ReDeeM is broadly applicable for refined lineage tracing in various biological problems, without requiring engineering. (11/n)
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Using ReDeeM, we built a cell-state aware single-cell phylogenetic tree of human hematopoiesis. We found combined mitochondrial mutations can largely reconstruct the hierarchical organization of the blood cell type origins. (5/n)
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@Li_Li_666
@YanHu41082612
@ShouwenW
@FD_Camargo
@BCHStemCell
@HSCRB
@harvardstemcell
Congratulations, Lili and colleagues!
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Deeply grateful to my mentors
@FulaiJin
and
@yan_yan_li
for their guidance. A huge shoutout to co-first authors
@axg826
and
@shanshanzhang
for their relentless dedication, and a big thank you to all our colleagues for their invaluable contributions.
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@jmartinrufino
@bloodgenes
@frdelpino
@DFBC_PedCare
@BBS_Harvard
@broadinstitute
Huge congrats, Jorge!!
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Congratulations, Julia! Incredible resource!
Thrilled to share my primary PhD work: a Transcription Factor Atlas for understanding gene regulation and cell engineering
@CellCellPress
. We created a comprehensive TF ORF library and applied it to profile resulting expression changes. A thread 1/X
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Interesting idea(attempt) to study a phenotype thcaused by multiple genes in complex relationships
PRISM, a new
#CRISPR
#screening
technology, enables unbiased perturbations of
#transcriptionalnetworks
. PRISM was used to reveal genes that protect models of
#Parkinson
’s disease from
#alphasynuclein
-induced toxicity.
@MolecularCell
-->
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@JiaruiMi
Thanks! That's a great question! S4C is the population transcriptionally most closely bridge to both endo/non-endocrine. And S4C actually shows PDX1+/SOX9+/GATA4-. So I think S4C is very likely the "bipotent trunk". But we'd need lineage/clonal info to make sure of that.
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@carninci
Very interesting! Wonder the fraction of rRNA using the random primer? Any tricks needed to avoid the rRNA to saturate the library? Thanks!
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@colonelragnar
@Nature
@JswLab
@bloodgenes
Thank you
@colonelragnar
!!! we are excited about both normal tissue homeostasis from adult stem cells and disease progression such as cancer evolution.
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Interesting story
@eLife
on gain of enhancers by MMR-mutations in colon cancer. Congratulations, my friend Stevephen Hung!!
Check out our lab's latest paper
@eLife
on MMR-mutations as enhancer activators in colon cancer. Couldn't be more pleased with their review process. Special congrats to lead author and MD-PhD student Stevephen Hung. As always, feedback is welcome.
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