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Lineage tracing of human development through somatic mutations

Spencer Chapman, Michael, Ranzoni, Anna Maria, Myers, Brynelle, Williams, Nicholas, Coorens, Tim H. H., Mitchell, Emily, Butler, Timothy, Dawson, Kevin J., Hooks, Yvette, Moore, Luiza, Nangalia, Jyoti, Robinson, Philip S., Yoshida, Kenichi, Hook, Elizabeth, Campbell, Peter J., Cvejic, Ana·2021·Nature
DOI 10.1038/s41586-021-03548-6
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Fig.1 Experimental workflow and phylogenetic trees. a, Single HSPCs were isolated from an 8 pcw human foetal liver and from 18 pcw matched foetal liver and two femurs. Single-cell derived colonies were expanded in vitro and sequenced by WGS. Somatic mutations identified
Fig.1 Experimental workflow and phylogenetic trees. a, Single HSPCs were isolated from an 8 pcw human foetal liver and from 18 pcw matched foetal liver and two femurs. Single-cell derived colonies were expanded in vitro and sequenced by WGS. Somatic mutations identifiedCC-BY · From the PDF
Image 2
CC-BY · From the PDF
Fig. 3 Timing of divergence of embryonic and extra-embryonic lineages during development. a, Phylogenetic tree showing the clonal relationships of 8 pcw HSPCs. Mutations identified in HSPCs by WGS that were also detected in non-haematopoietic tissues are coloured on the tree according to the earliest diverging tissue in which the mutation was reliably detected. Branch lengths are proportional to the number of mutations accumulated. The tree is cut at 22 mutations to highlight the early branching of the tree. b, Diagram of main human developmental events. Lineage separation is coloured as per the phylogenetic tree. In brackets are examples of tissues collected from each embryonic lineage. ICM, inner cell mass. c, Bar plot showing the minimum number of HSPC antecedents present at the time of divergence of different developmental lineages. d, Heatmap representation of the targeted sequencing data. Each column represents an individual mutation, and each row a single tissue. The colour shows the VAF of the mutation in that tissue with grey indicating that it was not detected. The tissues are clustered using soft cosine similarity (see methods). e, Line plot showing lineage loss of microdissected tissues at different times (represented as cell
Fig. 3 Timing of divergence of embryonic and extra-embryonic lineages during development. a, Phylogenetic tree showing the clonal relationships of 8 pcw HSPCs. Mutations identified in HSPCs by WGS that were also detected in non-haematopoietic tissues are coloured on the tree according to the earliest diverging tissue in which the mutation was reliably detected. Branch lengths are proportional to the number of mutations accumulated. The tree is cut at 22 mutations to highlight the early branching of the tree. b, Diagram of main human developmental events. Lineage separation is coloured as per the phylogenetic tree. In brackets are examples of tissues collected from each embryonic lineage. ICM, inner cell mass. c, Bar plot showing the minimum number of HSPC antecedents present at the time of divergence of different developmental lineages. d, Heatmap representation of the targeted sequencing data. Each column represents an individual mutation, and each row a single tissue. The colour shows the VAF of the mutation in that tissue with grey indicating that it was not detected. The tissues are clustered using soft cosine similarity (see methods). e, Line plot showing lineage loss of microdissected tissues at different times (represented as cellCC-BY · From the PDF
Fig. 4 Representation of haematopoietic lineages in developmentally-defined nonhaematopoietic tissues. a, Line plot showing the fraction of captured haematopoietic lineages in the 8 pcw phylogeny that are also detected in non-haematopoietic post-gastrulation tissues, grouped by germ layer. This is plotted over successive generations, during which the total number of lineages increases, but the proportion of lineages detected decreases. b-d, 8 pcw phylogenetic trees highlighting mutations detected in HSPCs that were shared with b, ectoderm-derived tissues, c, mesoderm-derived tissues and d, endoderm-derived tissues. The fraction of cells deriving from each lineage is plotted on a donut plot, with the black line representing the median cell fraction, and the dark and light blue segments representing the
Fig. 4 Representation of haematopoietic lineages in developmentally-defined nonhaematopoietic tissues. a, Line plot showing the fraction of captured haematopoietic lineages in the 8 pcw phylogeny that are also detected in non-haematopoietic post-gastrulation tissues, grouped by germ layer. This is plotted over successive generations, during which the total number of lineages increases, but the proportion of lineages detected decreases. b-d, 8 pcw phylogenetic trees highlighting mutations detected in HSPCs that were shared with b, ectoderm-derived tissues, c, mesoderm-derived tissues and d, endoderm-derived tissues. The fraction of cells deriving from each lineage is plotted on a donut plot, with the black line representing the median cell fraction, and the dark and light blue segments representing theCC-BY · From the PDF
Image 5
CC-BY · From the PDF
Extended Data Fig. 2 | Sample contamination and sequencing coverage. a, Box plot showing the percentage of human sequencing reads, prior to the exclusion of contaminating mouse reads from the feeder layer. b, Dot plot showing, for each colony of the two foetuses, the final sequencing coverage, post-exclusion of mouse reads, against the percentage of human reads. c, Box plot showing final sample coverage for the two foetuses. d, Dot plot showing the uncorrected SNV burden per colony against sample coverage. e, Dot plot showing the corrected SNV burden per colony against sequencing coverage. f, Dot plot showing the uncorrected indel burden per colony against sequencing coverage. SNVs = single nucleotide variations.
Extended Data Fig. 2 | Sample contamination and sequencing coverage. a, Box plot showing the percentage of human sequencing reads, prior to the exclusion of contaminating mouse reads from the feeder layer. b, Dot plot showing, for each colony of the two foetuses, the final sequencing coverage, post-exclusion of mouse reads, against the percentage of human reads. c, Box plot showing final sample coverage for the two foetuses. d, Dot plot showing the uncorrected SNV burden per colony against sample coverage. e, Dot plot showing the corrected SNV burden per colony against sequencing coverage. f, Dot plot showing the uncorrected indel burden per colony against sequencing coverage. SNVs = single nucleotide variations.CC-BY · From the PDF
Extended Data Fig. 3 | Mutation validation. Histograms showing variant allele fraction (VAF) of a, shared mutations with targeted sequencing depth ≥8× in the 8 pcw foetus, b, shared mutations with targeted sequencing depth ≥8× in the 18 pcw foetus, c, private mutations with targeted sequencing depth ≥8× in the 8 pcw foetus, d, private mutations with a high read depth ≥40× in the 8 pcw foetus, e, private mutations with depth ≥8× in the 18 pcw foetus, f, private mutations with a high read depth ≥40× in the 18 pcw foetus. Almost all shared mutations fitted a single clonal distribution. Private mutation distributions were best explained by a mixture of
Extended Data Fig. 3 | Mutation validation. Histograms showing variant allele fraction (VAF) of a, shared mutations with targeted sequencing depth ≥8× in the 8 pcw foetus, b, shared mutations with targeted sequencing depth ≥8× in the 18 pcw foetus, c, private mutations with targeted sequencing depth ≥8× in the 8 pcw foetus, d, private mutations with a high read depth ≥40× in the 8 pcw foetus, e, private mutations with depth ≥8× in the 18 pcw foetus, f, private mutations with a high read depth ≥40× in the 18 pcw foetus. Almost all shared mutations fitted a single clonal distribution. Private mutation distributions were best explained by a mixture ofCC-BY · From the PDF
Extended Data Fig. 4 | Laser-capture microdissected tissues. Representative histological slides of tissue structures with different developmental origins. Slides were stained with haematoxylin and eosin prior to microdissection. a, Structures microdissected from the 8 pcw sample included: mesodermal core and syncytiotrophoblast from the placenta, blood circulating in the heart, muscle from the heart, tubules from the kidney, epithelium from the gut, epidermis from the skin, vertebral disc from the vertebrae. b, Structures microdissected from the 18 pcw sample included: epidermis and peripheral nerves from the skin, muscle from the heart and glomeruli from the kidney.
Extended Data Fig. 4 | Laser-capture microdissected tissues. Representative histological slides of tissue structures with different developmental origins. Slides were stained with haematoxylin and eosin prior to microdissection. a, Structures microdissected from the 8 pcw sample included: mesodermal core and syncytiotrophoblast from the placenta, blood circulating in the heart, muscle from the heart, tubules from the kidney, epithelium from the gut, epidermis from the skin, vertebral disc from the vertebrae. b, Structures microdissected from the 18 pcw sample included: epidermis and peripheral nerves from the skin, muscle from the heart and glomeruli from the kidney.CC-BY · From the PDF
Extended Data Fig. 5 | Mutation burden of single-cell derived colonies. Histograms showing: a, SNV burden per single-HSPC derived colony for the 8 pcw and 18 pcw foetuses, corrected for both the proportion of private mutations that are acquired in vitro, and for sample sensitivity. b, Indel burden per single-HSPC derived colony for the 8 pcw and 18 pcw foetuses, with no correction applied. c, Mean numbers of private and shared SNVs per colony for each foetus.
Extended Data Fig. 5 | Mutation burden of single-cell derived colonies. Histograms showing: a, SNV burden per single-HSPC derived colony for the 8 pcw and 18 pcw foetuses, corrected for both the proportion of private mutations that are acquired in vitro, and for sample sensitivity. b, Indel burden per single-HSPC derived colony for the 8 pcw and 18 pcw foetuses, with no correction applied. c, Mean numbers of private and shared SNVs per colony for each foetus.CC-BY · From the PDF
Extended Data Fig. 6 Genomic distribution of identified somatic mutations. a, Bar plot showing the proportion of variants mapping to different genomic features. b, Plot showing the
Extended Data Fig. 6 Genomic distribution of identified somatic mutations. a, Bar plot showing the proportion of variants mapping to different genomic features. b, Plot showing theCC-BY · From the PDF
Image 11
CC-BY · From the PDF
Image 12
CC-BY · From the PDF
Extended Data Fig. 9 | High level of intermixing of 18 pcw HSPCs among fetal liver and two sites of bone marrow. a, Ultrametric phylogenetic tree of 18 pcw HSPCs with branches coloured by the tissue from which HSPCs bearing the mutations were isolated. Black branches indicate that cells were found in more than one tissue, coloured branches indicate cells were unique to one specific tissue. b, Analysis of molecular variance used to formally test for clustering on the phylogeny of HSPCs isolated from the same tissue. The histogram shows the null distribution used to detect clustering. Distributions were obtained by randomly permuting which cells were assigned to which tissue. The observed value of the phi statistic is shown as a red line, with the p-value indicating no statistically significant clustering by tissue.
Extended Data Fig. 9 | High level of intermixing of 18 pcw HSPCs among fetal liver and two sites of bone marrow. a, Ultrametric phylogenetic tree of 18 pcw HSPCs with branches coloured by the tissue from which HSPCs bearing the mutations were isolated. Black branches indicate that cells were found in more than one tissue, coloured branches indicate cells were unique to one specific tissue. b, Analysis of molecular variance used to formally test for clustering on the phylogeny of HSPCs isolated from the same tissue. The histogram shows the null distribution used to detect clustering. Distributions were obtained by randomly permuting which cells were assigned to which tissue. The observed value of the phi statistic is shown as a red line, with the p-value indicating no statistically significant clustering by tissue.CC-BY · From the PDF

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Cited by

Metadata

Authors
Spencer Chapman, M., Ranzoni, A. M., Myers, B., Williams, N., Coorens, T. H. H., Mitchell, E., Butler, T., Dawson, K. J., Hooks, Y., Moore, L., Nangalia, J., Robinson, P. S., Yoshida, K., Hook, E., Campbell, P. J., & Cvejic, A.
Venue
Nature
Publisher
Springer Science and Business Media LLC
Published
2021-05-12
Volume
595
Issue
7865
Pages
85-90
ISSN
  • 0028-0836
  • 1476-4687
DOI
10.1038/s41586-021-03548-6
Cited by
167
References
6
Language
en
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