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1
The evolution of two transmissible leukaemias
colonizing the coasts of Europe
Alicia L. Bruzos1,2,3,†, Martín Santamarina1,2,3,†, Daniel García-Souto1,2,3,4,†, Seila Díaz1,†,
Sara Rocha5,†, Jorge Zamora1,‡, Yunah Lee6,‡, Alejandro Viña-Feás1,3,‡, Michael A. Quail4,
Iago Otero1,2,3, Ana Pequeño-Valtierra1,3, Javier Temes1,3, Jorge Rodriguez-Castro1,3,
Antonio Villanueva7, Damián Costas7, Rosana Rodríguez7, Tamara Prieto5,8,9, Laura Tomás5,8,
Pilar Alvariño5,8, Juana Alonso5,8, Asunción Cao10, David Iglesias10, María J. Carballal10,
Ana M. Amaral11, Pablo Balseiro12,13, Ricardo Calado14, Bouchra El Khalfi15, Urtzi Izagirre16,17,
Xavier de Montaudouin18, Nicolas G. Pade19, Ian Probert20, Fernando Ricardo14, Pamela Ruiz16,17,
Maria Skazina21, Katarzyna Smolarz22, Juan J. Pasantes7,23, Antonio Villalba10,16,24,
Zemin Ning4, Young Seok Ju6, David Posada5,8,23, Jonas Demeulemeester25,26,27,
Adrian Baez-Ortega4,28,#,*, Jose M. C. Tubio1,2,3,#,*
1Genomes and Disease, Centre for Research in Molecular Medicine and Chronic Diseases (CiMUS),
Universidade de Santiago de Compostela, Santiago de Compostela 15706, Spain.
2Department of Zoology, Genetics and Physical Anthropology, Universidade de Santiago de
Compostela, Santiago de Compostela 15706, Spain.
3Instituto de Investigaciones Sanitarias de Santiago de Compostela (IDIS), Santiago de Compostela
15706, Spain.
4Wellcome Sanger Institute, Hinxton CB10 1SA, United Kingdom.
5Biomedical Research Centre (CINBIO), Universidade de Vigo, Vigo 36310, Spain.
6Graduate School of Medical Science and Engineering, Korea Advanced Institute of Science and
Technology (KAIST), Daejeon 34141, Republic of Korea.
7Centro de Investigación Mariñas (CIM-ECIMAT), Universidade de Vigo, Vigo 36331, Spain.
8Galicia Sur Health Research Institute (IIS Galicia Sur), SERGAS-UVIGO, Vigo 36312, Spain.
9New York Genome Center, New York 10013, USA.
10Centro de Investigacións Mariñas (CIMA), Consellería do Mar, Xunta de Galicia, Vilanova de
Arousa 36620, Spain.
11Centro de Ciencias do Mar do Algarve (CCMAR), Universidade do Algarve, Faro 8005-139,
Portugal.
12Department of Biological Sciences, University of Bergen, Bergen 5006, Norway.
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13NORCE AS, Bergen 5008, Norway.
14ECOMARE, Centre for Environmental and Marine Studies (CESAM) & Department of Biology,
University of Aveiro, Aveiro 3810-193, Portugal.
15Laboratory of Physiopathology, Hassan II University of Casablanca, Casablanca 20100, Morocco.
16Research Centre for Experimental Marine Biology and Biotechnology (PiE-UPV/EHU), University
of the Basque Country (UPV/EHU), Plenzia-Bitzkaia 48620, Spain.
17Cell Biology in Environmental Toxicology Research Group, University of the Basque Country
(UPV/EHU), Leioa-Bizkaia 48940, Spain.
18UMR EPOC5805, University of Bordeaux, Arcachon 33120, France.
19European Marine Biology Resources Centre (EMBRC-ERIC), Paris 75252, France.
20FR2424 Station Biologique de Roscoff, Sorbonne University/CNRS, Roscoff 29682, France.
21Department of Applied Ecology, St Petersburg State University, St Petersburg 199178, Russia.
22Department of Marine Ecology, University of Gdańsk, Gdynia 80-587, Poland.
23Department of Biochemistry, Genetics and Immunology, Universidade de Vigo, Vigo 36310, Spain.
24Department of Life Sciences, Universidad de Alcalá, Alcalá de Henares 28871, Spain.
25VIB–KU Leuven Center for Cancer Biology, Leuven 3000, Belgium.
26Department of Oncology, KU Leuven, Leuven 3000, Belgium.
27The Francis Crick Institute, London NW1 1AT, United Kingdom.
28Magdalene College, University of Cambridge, Cambridge CB3 0AG, United Kingdom.
†These authors contributed equally to this work.
‡These authors contributed equally to this work.
#These authors contributed equally to this work.
*Corresponding authors.
Address for correspondence:
Dr Jose M. C. Tubio
Genomes and Disease,
Centre for Research in Molecular Medicine and Chronic Diseases (CiMUS),
Universidade de Santiago de Compostela,
Santiago de Compostela 15706, Spain
e-mail: jose.mc.tubio@usc.es
Dr Adrian Baez-Ortega
Cancer, Ageing and Somatic Mutation Programme,
Wellcome Sanger Institute,
Wellcome Genome Campus,
Hinxton CB10 1SA, United Kingdom
e-mail: ab2324@cam.ac.uk
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3
Abstract
Transmissible cancers are malignant cell clones that spread among individuals through transfer of living
cancer cells. Several such cancers, collectively known as bivalve transmissible neoplasia (BTN), are
known to infect and cause leukaemia in marine bivalve molluscs. This is the case of BTN clones
affecting the common cockle, Cerastoderma edule, which inhabits the Atlantic coasts of Europe and
north-west Africa. To investigate the origin and evolution of contagious cancers in common cockles,
we collected 6,854 C. edule specimens and diagnosed 390 cases of BTN. We then generated a reference
genome for the species and assessed genomic variation in the genomes of 61 BTN tumours. Analysis
of tumour-specific variants confirmed the existence of two cockle BTN lineages with independent
clonal origins, and gene expression patterns supported their status as haemocyte-derived marine
leukaemias. Examination of mitochondrial DNA sequences revealed several mitochondrial capture
events in BTN, as well as co-infection of cockles by different tumour lineages. Mutational analyses
identified two lineage-specific mutational signatures, one of which resembles a signature associated
with DNA alkylation. Karyotypic and copy number analyses uncovered genomes marked by pervasive
instability and polyploidy. Whole-genome duplication, amplification of oncogenes CCND3 and MDM2,
and deletion of the DNA alkylation repair gene MGMT, are likely drivers of BTN evolution.
Characterization of satellite DNA identified elements with vast expansions in the cockle germ line, yet
absent from BTN tumours, suggesting ancient clonal origins. Our study illuminates the evolution of
contagious cancers under the sea, and reveals long-term tolerance of extreme instability in neoplastic
genomes.
Introduction
Transmissible cancers are clonal somatic cell lineages that spread between individuals via direct transfer
of living tumour cells, in a process analogous to cancer metastasis (1, 2). Naturally occurring
transmissible cancers have been identified in dogs (3–5), Tasmanian devils (6–8) and, more recently,
several species of marine bivalve molluscs (9–14). To date, eight transmissible cancer lineages,
collectively known as bivalve transmissible neoplasia (BTN), have been described in bivalves, probably
spreading via transfer of free-floating cells in seawater. BTN infection causes a leukaemia-like disease
termed disseminated neoplasia (DN), where neoplastic cells proliferate and accumulate in the host’s
haemolymph and solid tissues (15). Although DN is generally fatal, slow progression and remission
have been described (16, 17).
Among the species affected by DN is the common cockle, Cerastoderma edule. This marine bivalve is
distributed along the Atlantic coasts of Europe and north-west Africa, being typically found in tidal flats
at bays and estuaries (18). Adult cockles bury themselves in the seabed sediment and use their syphons
and gills to filter seawater for sustenance. DN in common cockles was first documented 40 years ago
in Ireland (19), and later identified in other European countries (15). A genetic study recently provided
evidence that DN in C. edule is caused by transmissible cancer, and suggested the existence of at least
two BTN clones in this species (10). Nevertheless, the origins and evolution of cockle BTN lineages
remain entirely unexplored.
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4
Here, we present the first comprehensive study of the genomes of BTN clones affecting C. edule in
Europe. We sampled thousands of common cockle specimens across 11 countries, obtained a
chromosome-level reference genome for the species, and used it to catalogue the genomic variation in
61 BTN tumours identified in these animals. Combining histopathology, cytogenetics, and sequencing
of whole genomes and transcriptomes, our study illuminates the evolutionary history of the marine
leukaemias that have colonized European cockle populations.
Prevalence of disseminated neoplasia in common cockles
To investigate the current prevalence of DN in C. edule, we collected 6,854 specimens at 36 locations
from 11 countries along the Atlantic coasts of Europe and north Africa between 2016 and 2021 (Fig.
1A; Table S1). This included intensive sampling on the coasts of Ireland and Galicia (north-west
Spain), two regions where high prevalence of DN has been reported in the past (20–22).
Cytohistological examination of haemolymph and solid tissues revealed that 5.7% (390/6,854) of
specimens were infected by abnormal circulating cells displaying the features of DN (Fig. 1A; Table
S1). High overall prevalence was observed in Portugal (17.6%), Ireland (7.4%) and Spain (6.4%), with
lower prevalence found in the United Kingdom (3.6%) and France (1.1%; Fig. S1); no DN cases were
detected in the remaining six countries (Germany, Denmark, Morocco, the Netherlands, Norway,
Russia). Twenty percent (77/390) of neoplastic specimens presented a severe form of the disease (stage
N3), characterized by high levels (>75%) of neoplastic cells in the haemolymph and massive tissue
infiltration foci; 26% (102/390) presented an intermediate form (stage N2), distinguished by 15–75%
of neoplastic cells in the haemolymph and presence of small infiltration foci in one or more organs; the
remaining individuals (53%, 208/390) were diagnosed with a mild form (stage N1), where low levels
(<15%) of neoplastic cells circulate in the haemolymph and infiltrate solid tissues in small numbers
(22) (Fig. S2; Table S2).
Reference genome and transcriptome of the common cockle
As an initial step in our genomic study of cockle DN, we applied multiplatform DNA sequencing to
obtain a reference assembly of the C. edule genome (Fig. S3). As our reference specimen, we selected
a healthy adult male cockle (Fig. 1B) carrying a standard karyotype with 19 chromosome pairs. Hybrid
genome assembly yielded a chromosome-level reconstruction of the cockle nuclear genome into 19
scaffolds (N50=39.6 megabases, Mb; Table S3), with an additional 14.9-kilobase (kb) scaffold
containing the mitochondrial genome sequence. Haploid genome size was estimated at 790 Mb, with a
G+C content of 35.6%. We additionally employed RNA sequencing data from seven tissues to
reconstruct a 290-Mb reference transcriptome displaying 98.8% completeness in metazoan gene content
(Table S3). Gene annotation resulted in a 42-Mb exome with 14,055 protein-coding genes. While this
protein-coding exome constitutes 5.3% of the total nuclear genome size, repetitive sequences comprise
46.2% of the genome, with long interspersed nuclear elements (LINEs) being the most frequent type of
transposable element among annotated repeats (Fig. S4; Table S4).
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5
Figure 1. Distribution, origins and clonal structure of transmissible neoplasia in common cockles. A,
Numbers of healthy and neoplastic C. edule cockles collected at each sampling location, with overall cancer
prevalence per location for 2016–2021 (left). Map shows sampling locations and geographic distribution of the
species. B, Photographs of the individual from which the reference C. edule genome was assembled (scale bar,
10 mm). C, Micrographs of histological sections from healthy and DN-affected cockle tissues. Images in the left-
hand column show healthy connective tissue surrounding the male gonadal follicle (top) and connective tissue
heavily infiltrated by type A and type B DN cells (scale bars, 50 µm). Images in the right-hand column show
details of normal haemocytes (top), type A and type B DN cells (scale bar, 10 µm). D, Phylogenetic tree inferred
from BTN-specific SNVs in 10 high-purity tumour samples, showing concordance between histological DN types
A and B and two clonal transmissible cancer lineages, CedBTN1 and CedBTN2. Numbers of SNVs and dN/dS
ratios are provided for different sections of the tree. All nodes have bootstrap support values of 100 (n=1000
replicates). Scale bar indicates phylogenetic distance (SNVs per site). E, Principal component analysis of gene
expression for genes with tissue-specific expression in normal cockle tissues and DN samples, indicating a
clustering of DN (red shading) with healthy haemolymph (blue shading).
Algarve
Aveiro
Oualidia
Wales
Plymouth
Roscoff
Arcachon
Slikken van Viane
Nykobing Mors
Hejeltefjorden
Sylt
Noia
Baiona
Muros
Barallobre
Espasante
Moaña
Combarro
Placeres
Carril
Grove
Camariñas
Río Anllóns
Westport
Cork
Inch Beach
Dublin
Wexford
Veno Limfjorden
Murmansk
Bodoe
Bilbao
Loch Gair
Tràig Mhòr
Strollamus
PACE
PVCE
MOCE
UGCE
UDCE
FRCE
FACE
HSCE
DNCE
NHCE
ASCE
ENCE
EYCE
EUCE
EOCE
EECE
EMCE
EACE
ELCE
ECCE
EGCE
EICE
EPCE
IWCE
ICCE
ITCE
IDCE
IXCE
NBCE
DVCE
RMCE
ULCE
UTCE
USCE
EBCE
Galicia, Spain
Ireland
Cerastoderma edule distribution
Cancer detected
No cancer detected Sampling points
Countries with cancer cases
Countries without cancer cases
Dalnye Zelentsy
RDCE
B
C
A
CedBTN2
(Type B)
5×10–4
A1
1,081,955 SNVs
dN/dS = 0.58
UGCE17/2401H
EICE18/887H
EPCE18/848H
FRCE17/701H
PACE17/421H1
PACE17/433H
PVCE17/1402H
PVCE17/1247H
EUCE18/1024H
EICE18/889H
Reference
1,541,008 SNVs
dN/dS = 0.24
A0
130,432 SNVs
dN/dS = 0.96
A2
524,139 SNVs
dN/dS = 0.58
612,575 SNVs
dN/dS = 0.94
CedBTN1
(Type A)
D
E
−0.4
−0.2
0.0
0.2
−0.2 0.0 0.2
PC1 (33.35%)
PC2 (13.16%)
Type AType B Healthy
FRCE
FACE
EYCE
EUCE
EPCE
EOCE
ENCE
EMCE
ELCE
EICE
EGCE
EECE
ECCE
EBCE
EACE
DVCE
DNCE
ASCE
UTCE
USCE
ULCE
UGCE
UDCE
RMCE
RDCE
PVCE
PACE
NHCE
NBCE
MOCE
IXCE
IWCE
ITCE
IDCE
ICCE
HSCE
Cancer prevalence (%)
Number of individuals
Sampling location
Cancer
Healthy
Prevalence
0 200 400 600 0 200 400 600
0 10 20 0 10 20 3030
Adductor muscle
Foot
Mantle Gonad
Digestive system
Gills
Haemolymph
Type A
Type B
Normal samples
Tumour samples
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Two transmissible cancer lineages propagate through cockle populations
Traditionally, two distinct classes of cockle DN, termed types ‘A’ and ‘B’, have been described through
cytohistological methods, on the basis of differences in tumour cell size and morphology (21) (Fig. 1C).
A previous analysis of microsatellite variation and single-nucleotide variants (SNVs) in both
mitochondrial DNA (mtDNA) and one nuclear gene provided evidence that these DN types represent
two transmissible cancer lineages (10), although it is possible that further lineages, as well as non-
transmissible cases of cockle DN, exist.
To further investigate the origins and evolution of cockle BTN, we performed whole-genome
sequencing of neoplastic haemolymph samples from 61 individuals diagnosed with DN (Table S5).
Ten of these samples, presenting high (≥90%) tumour purity, were designated as a BTN ‘golden set’,
and used to identify a collection of high-confidence candidate somatic variants. We also sequenced
matched tissue samples from 40 host individuals and 462 non-neoplastic specimens collected across the
species’ geographic range (Table S5). After accounting for host DNA contamination and common
germline polymorphisms, we identified a total of 4.3 million SNVs (2.5–3.1 million SNVs per sample;
Table S6) and 0.7 million short insertions and deletions (indels). This ‘BTN-specific’ variant set
includes both somatic variants in each BTN lineage and ancestral germline polymorphisms (from each
lineage’s founder individual) which were absent from our panel of 462 non-neoplastic cockles.
We used BTN-specific SNVs to reconstruct a tumour phylogenetic tree, which split the 10 ‘golden set’
tumours into two divergent lineages (Fig. 1D), consistently corresponding to the two histological types
of cockle DN (Fig. S5). We hereafter refer to these two lineages of C. edule BTN, respectively
corresponding to DN types A and B, as CedBTN1 and CedBTN2. To assess the quality of our variant
set and confirm the independent origins of both BTN lineages, we estimated the ratio of nonsynonymous
to synonymous mutation rates (dN/dS) (23, 24) along the phylogenetic tree (Fig. 1D). The dN/dS ratios
for variants shared by all 10 tumours (ancestral variant set ‘A0’) and variants shared by all tumours in
each lineage (sets ‘A1’ and ‘A2’) indicate that these sets contain a large fraction of germline
polymorphisms from two separate founder individuals (dN/dS 0.24 for A0, 0.58 for A1, 0.58 for A2).
In contrast, the dN/dS for the terminal branches approximates a neutral value of 1.0 (0.96 for CedBTN1,
0.94 for CedBTN2), as expected for pure sets of somatic mutations (24). Accordingly, the dN/dS of
variants found in only one tumour (private variants) is 1.00 (Table S7).
Additionally, we performed principal component analysis on a set of germline polymorphisms
genotyped across the 10 ‘golden set’ tumours and 100 non-neoplastic cockles covering all sampled
populations (Fig. S6). This analysis split the tumours into two divergent clusters matching CedBTN1
and CedBTN2, and set apart from two non-neoplastic sample clusters representing relatively divergent
groups of cockle populations from northern and southern Europe (25). This result suggests that CedBTN
clones are highly divergent both from each other and from modern cockle populations, further
supporting two independent origins. Nevertheless, analysis of sequence mapping data shows that the
fractions of sequence reads aligning against the C. edule reference genome in BTN samples (97.4–
98.1%, ‘golden set’ samples) are comparable to those for 462 non-neoplastic cockles (interquartile
range 97.1–97.8%) and substantially higher than fractions for cockles of the closest known species, C.
glaucum (48.3–60.4%, six samples), consistent with both clones having arisen in C. edule animals.
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Haemocytic origin of cockle transmissible neoplasia
The ontogeny of bivalve DN is a long-standing question with relevance for the biology and evolution
of BTN. The fact that DN cells are observed in the circulatory system and share morphological features
with haemocytes has traditionally led to their consideration as neoplastic haemocytes (15).
Nevertheless, some studies have proposed alternative tissues of origin for these cancers, including the
gonad follicles or gill epithelium (15).
To shed light on the origins of CedBTN lineages, we sequenced the transcriptomes of haemolymph
samples from eight cockles diagnosed with advanced stages DN, and a collection of seven tissues
(adductor muscle, mantle, foot, digestive system, gills, gonad and haemolymph) from 28 non-neoplastic
animals (Table S5). Gene expression analysis for a set of 420 genes with tissue-specific expression (60
genes per tissue type) indicated a consistent gene expression profile for type A and type B DN samples,
which is close to that of non-neoplastic haemolymph samples and divergent from those of all other
tissues (Fig. 1D; Fig. S7; Table S8). This finding suggests that cockle BTN clones are cancers of the
haemolymphatic system, derived from somatic haemocytes or haemic progenitor cells. This recurrent
cellular origin may reflect an exclusive capability of malignant haemocytes to exploit the transmission
opportunities offered by the open circulatory system of bivalves.
Mitochondrial transfer delineates the clonal structure of CedBTN
To explore the evolutionary history of CedBTN at the mitochondrial level, we identified SNVs in the
mtDNA of 51 haemolymph samples from neoplastic cockles, 40 matched-host tissue samples and 168
non-neoplastic cockle samples. In neoplastic animals, sequencing data showed two mtDNA haplotypes
at distinct variant allele fractions (VAFs), corresponding to the host and CedBTN mitochondrial
genomes. Combining tumour purity and mtDNA VAF information to deconvolute the mtDNA
haplotypes within each sample, we identified nine distinct tumour haplotypes (six in CedBTN1 and
three in CedBTN2), each distinguished by a specific set of mtDNA variants (Fig. 2A; Table S6; Table
S9).
The findings above suggested the existence of nine CedBTN mtDNA lineages. This was confirmed
through phylogenetic reconstruction via maximum likelihood (ML) and Bayesian methods (Fig. 2B;
Fig. S8; Fig. S9). The presence of multiple mtDNA lineages within each CedBTN clone indicates that
mitochondria from transient hosts have repeatedly been acquired by these tumours, as previously
described for other transmissible cancers (26, 27). We therefore labelled these mtDNA lineages after
putative mitochondrial horizontal transfer (HT) events (BTN1-HT1 to -HT6 and BTN2-HT1 to -HT3),
although it is currently impossible to ascertain whether two of these lineages represent the original
mtDNA haplotypes of the CedBTN founder individuals. The correspondence between mtDNA and
nuclear lineages was supported by a phylogenetic tree inferred from the genotypes of nuclear BTN-
specific SNVs across the entire set of 61 sequenced tumours (Fig. S10). Furthermore, tumours from
distinct mtDNA lineages within the same CedBTN clone presented no evident cytohistological
differences (Fig. S11; Table S10). We evaluated the potentially independent origins of the nine mtDNA
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lineages using three topology testing methods on the mtDNA phylogenies (Shimodaira–Hasegawa [SH]
and approximately unbiased [AU] tests for the ML tree, posterior odds for the Bayesian tree), which
consistently supported independent origins for eight of the lineages (P=0 for SH, P<5×10–5 for AU,
posterior odds=0).
Analyses of the geographic distribution of mtDNA haplotypes from tumours and their sister taxa
(defined as non-neoplastic samples derived from the same node in the phylogeny) provided insight into
the origins and spread of CedBTN mtDNA lineages. Firstly, although most tumour samples from the
same mtDNA lineage are usually found in the same geographic region (e.g. BTN1-HT1 in south
Portugal, BTN1-HT2 in France, BTN1-HT3 in Ireland), this is not the case for BTN2-HT2, for which
tumour specimens were collected in north-west Spain and Wales (Fig. 2C). Secondly, the geographic
ranges of tumours and their sister taxa may be expected to overlap (e.g. BTN1-HT3 and sister taxa in
Ireland), or at least be proximate (e.g. BTN1-HT2 in France and sister taxa in Spain and Portugal), yet
we observed four mtDNA lineages (BTN1-HT1, BTN1-HT2, BTN2-HT2, BTN2-HT3) occupying
regions distant from the ranges of their sister taxa (Fig. 2D). Two remarkable cases are BTN1-HT1 and
BTN2-HT3, for which tumours were found in Portugal and Spain, respectively, while their sister taxa
were sampled in Ireland, Germany, Denmark and Norway. Thirdly, the sister taxa of CedBTN2 mtDNA
lineages were almost invariably found in northern regions (Denmark, Germany, Norway and the
Netherlands), despite the fact that no CedBTN2 tumours were observed in this range (Fig. 2D; Fig.
S12). Although we cannot rule out an anthropogenic cause for some of these patterns, the geographic
structure of the mtDNA phylogeny suggests that CedBTN clones have spread over long distances along
the Atlantic coast of Europe, possibly through a gradual process of natural colonization. Host
mitochondria have been captured by CedBTN cells at different points in this process, potentially to
replace heavily mutated incumbent mtDNA (26, 28).
In addition to mtDNA SNVs, inspection of sequencing depths revealed three independent
amplifications spanning the control region of the mtDNA D-loop in CedBTN1, which are absent from
healthy cockles (Fig. S13). The amplified sequences share a common start motif and overlapping
microhomology at the boundaries, which is associated with imperfect DNA break repair (29). The
evolutionary significance of these recurrent amplifications is unclear: they may be neutral changes, or
the result of selfish selection at the mitochondrial level (27), or yet confer an advantageous phenotype
on BTN cells. Notably, similar D-loop amplifications have been identified in both BTN and non-
neoplastic samples from North American soft-shell clams (30), as well as human cancers (31).
Analysis of changes in mtDNA VAF across different tissues of the same animal revealed three cases in
which two CedBTN mtDNA lineages coexisted within the same host (Fig. S14). In one remarkable
animal (EICE18/910), VAF analysis revealed the presence of mtDNA haplotypes from both CedBTN1
and CedBTN2 lineages (Fig. 2E), with co-infection by both clones being confirmed through
histopathological identification of cell morphologies matching DN types A and B (Fig. 2F).
Histopathological re-evaluation of our tumour collection uncovered seven additional cases of co-
infection by both types of DN (Table S2). These findings suggest that, despite its extreme rarity in
mammalian transmissible cancers, host co-infection is a relatively frequent event in cockle BTN.
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Figure 2. Mitochondrial DNA phylogeny, mtDNA horizontal transfer and co-infection in CedBTN. A, Ancestral
mtDNA haplotypes identified in CedBTN samples, with ancestral SNVs (common to all samples carrying the haplotype)
arranged along the reference mtDNA sequence (x-axis). Potentially somatic SNVs (absent from non-neoplastic samples)
are shown in black. Potential mtDNA HT events associated with each haplotype in CedBTN1 (red) and CedBTN2
(purple) are labelled, with number of samples used to identify ancestral variants given in parentheses. Bar plot presents
numbers of potentially somatic (black) and total (grey) ancestral variants per haplotype; numbers are indicated next to
each bar. A schematic representation of the mtDNA gene annotation is shown at the bottom. B, Bayesian phylogenetic
tree of mtDNA haplotypes in normal and CedBTN samples, with identified tumour mtDNA lineages highlighted and
labelled. Branch lengths represent phylogenetic distance (scale bar given in C). C, Correspondence between mtDNA
phylogenetic tree and tumour sampling regions; map point colours denote CedBTN lineages as in B. Sampling points
in Galicia (north-west Spain) are grouped into northern and southern points. Scale bar indicates phylogenetic distance
(SNVs per site). D, Maps showing locations of tumours and normal sister taxa for five mtDNA lineages. E, VAF plot
evidencing co-infection of a host (EICE18/910) by cells from two mtDNA lineages, one from each CedBTN clone.
Three observed mtDNA haplotypes are shaded in different colours. F, Micrograph of histological section of gills from
EICE18/910, confirming co-infection by both CedBTN clones. Dilated efferent vessels are shown; vessels labelled ‘1’
and ‘2’ are mainly infiltrated by type A and type B neoplastic cells, respectively. Scale bar, 50 µm.
BTN2-HT2
BTN1-HT4
E
VAF
mtDNA coordinate (bp)
0.8
1
0.6
0.4
0.2
0
05000 10,000 15,000
Host haplotype
BTN haplotypes
Shared variants
CedBTN1
CedBTN2
Healthy/host
B
T
N
2
-
H
T
1
B
T
N
2
-
H
T
2
B
T
N
2
-
H
T
3
B
T
N
1
-
H
T
1
6
T
H
-
1
N
T
B
5
T
H
-
1
N
T
B
4
T
H
-
1
N
T
B
2
T
H
-
1
N
T
B
B
T
N
1
-
H
T
3
0.2 5
BTN2-HT3
BTN1-HT1
BTN2-HT2
BTN2-HT1
BTN1-HT3
BTN1-HT4
BTN1-HT5
BTN1-HT6
BTN1-HT2
BTN2-HT2
Location of tumours Location of sister taxa Location of tumours and sister taxa
B
D
C
BTN1-HT1 BTN1-HT2 BTN1-HT3
BTN2-HT3
0.1
F
21
A
Ancestral mtDNA SNVs
0 6000 10,000 14,943
8000
2000 4000 12,000
CO3ND1ND5CO2
ND6
ND4L
ND2
ND3
12S
rRNA
ATP6ND4
ATP8
16S rRNACYTBCOI
SNVs
0 40 80 120 160 200
BTN1-HT1 (5)
BTN1-HT2 (2)
BTN1-HT3 (2)
BTN1-HT4 (6)
BTN1-HT5 (2)
BTN1-HT6 (7)
BTN2-HT1 (2)
BTN2-HT2 (3)
BTN2-HT3 (3)
35 / 130
9 / 114
3 / 51
8 / 48
4 / 43
3 / 21
60 /
182
9 / 112
4 / 87
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10
Lineage-specific mutational processes operate in cockle BTN
To investigate the processes of DNA damage and repair causing mutations in CedBTN, we examined
patterns of SNVs and indels at particular sequence contexts, termed mutational signatures (32). The
mutational spectra of germline cockle SNVs and BTN-specific SNVs are broadly similar, the major
difference being a higher fraction of cytosine-to-thymine (C>T) substitutions at non-CpG sites in
CedBTN relative to the germ line (Fig. 3A). We assessed mutational processes across the CedBTN
phylogeny by defining six subsets of BTN-specific variants (Fig. 3B): SNVs shared by all samples from
each clone, but not shared between clones (two pre-divergence sets, ‘A1’ and ‘A2’; Fig. 1D); SNVs
shared by only some tumours in each clone (two non-private post-divergence sets); and SNVs present
in one tumour (two private sets). We also defined two germline sets: ancestral SNVs shared by both
CedBTN clones (ancestral set, ‘A0’), and SNVs identified in three non-neoplastic cockles. While the
two pre-divergence sets, containing mostly germline variants, present similar mutational spectra, the
largely somatic post-divergence sets exhibit notable differences, particularly in the C>T component
(Fig. 3B).
With the aim of quantifying the contribution of different mutational processes to these variant sets, we
applied a Bayesian approach to infer five mutational signatures de novo from their mutational spectra
(33) (Fig. 3C). Three of these signatures (SBS-A, SBS-B, SBS-C) are shared by germline and BTN-
specific sets, while the remaining two (SBS-D, SBS-E) are BTN-specific. Most signatures show
similarity to human mutational signatures, especially if the latter are corrected for the trinucleotide
composition of the human genome. Among the germline signatures, SBS-A probably corresponds to a
mixture of human signatures SBS1 (cosine similarity 0.84), caused by spontaneous deamination of 5-
methylcytosine at CpG sites (29, 34), and SBS5 (0.90), thought to arise from multiple endogenous
mutational processes (29, 35, 36); SBS-B resembles human SBS40 (0.79), possibly caused by the same
endogenous processes as SBS5 (35, 36); and SBS-C is similar to SBS8 (0.82), a signature associated
with DNA repair and replication errors in human cancers and absent from the human germ line (37,
38). Of the BTN-specific signatures, SBS-D resembles both SBS23 (0.86), a signature of unknown
aetiology described in human myeloid and brain tumours (29), and SBS11 (0.81), associated with the
alkylating chemotherapeutic agent temozolomide (32); the profile of SBS-E has no evident human
counterpart, the closest match being SBS40 (0.71).
To explore variation in the activity of mutational processes, we assessed mutational signature exposures
across the BTN phylogeny. Signatures SBS-D and SBS-E, while undetectable in germline variant sets,
are each predominantly associated with one BTN clone: whereas SBS-D dominates the spectrum of
CedBTN1 post-divergence mutations, SBS-E is mainly active in the CedBTN2 post-divergence set
(Fig. 3D; Table S11). We note that, while BTN-specific variant sets (including A0) present lower SBS-
A exposures relative to the cockle germ line, this may simply reflect disproportionate filtering of
variants at CpG sites, which are underrepresented relative to other sequence contexts in the cockle
genome.
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11
Figure 3. Mutational processes in CedBTN. A, Mutational spectra of germline SNVs in three healthy cockle
samples (left) and BTN-specific SNVs in 10 CedBTN samples (excluding the set of shared ancestral SNVs, A0
in Fig. 1D). The x-axis presents 96 mutation types in a trinucleotide context, coloured by base substitution type
(29). B, Mutational spectra of subsets of BTN-specific variants in CedBTN1 (top) and CedBTN2, including pre-
divergence variants (left; A1/A2), non-private post-divergence variants (centre) and private variants. The y-axis
presents number of mutations. C, Germline (top) and BTN-specific mutational signatures inferred from the spectra
shown in A and B (plus the A0 spectrum), and normalized to correct for the cockle genome trinucleotide
frequencies. The y-axis presents mutation probability. D, Contribution of each mutational signature to the SNVs
in each segment of the CedBTN phylogenetic tree (Fig. 1D) and in healthy samples. Bars for post-divergence
variant sets are depicted with greater width to denote collapsing of multiple internal branches of the tree. E,
Mutational spectra of germline indels in three healthy samples (left) and BTN-specific indels in 10 CedBTN
samples (excluding the shared ancestral set, A0). The x-axis presents 83 insertion/deletion types coloured by type
and length (29).
Inspection of indel spectra provided evidence for a variety of mutational processes in germline and
BTN-specific sets (Fig. 3E). Although not every observed pattern can be matched to a human signature,
germline indels appear to be enriched in signatures ID1 and ID2 (single-nucleotide deletions and
insertions at A/T homopolymers, caused by strand slippage during DNA replication (29)), as well as
ID9 and ID14 (single-nucleotide deletions and insertions at homopolymers, of unknown aetiology).
Mutations
Healthy (3 samples)
C>A C>G C>T T>A T>C T>G
0 400,000 800,000
C>A C>G C>T T>A T>C T>G
0 40,000 80,000
CedBTN
(10 samples, excluding A0)
ACA
ACC
ACG
ACT
CCA
CCC
CCG
CCT
GCA
GCC
GCG
GCT
TCA
TCC
TCG
TCT
ACA
ACC
ACG
ACT
CCA
CCC
CCG
CCT
GCA
GCC
GCG
GCT
TCA
TCC
TCG
TCT
ACA
ACC
ACG
ACT
CCA
CCC
CCG
CCT
GCA
GCC
GCG
GCT
TCA
TCC
TCG
TCT
ATA
ATC
ATG
ATT
CTA
CTC
CTG
CTT
GTA
GTC
GTG
GTT
TTA
TTC
TTG
TTT
ATA
ATC
ATG
ATT
CTA
CTC
CTG
CTT
GTA
GTC
GTG
GTT
TTA
TTC
TTG
TTT
ATA
ATC
ATG
ATT
CTA
CTC
CTG
CTT
GTA
GTC
GTG
GTT
TTA
TTC
TTG
TTT
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
T
T
T
T
T
T
T
T
T
T
T
T
T
T
T
T
T
T
T
T
T
T
T
T
T
T
T
T
T
T
T
T
T
T
T
T
T
T
T
T
T
T
T
T
T
T
T
T
ACA
ACC
ACG
ACT
CCA
CCC
CCG
CCT
GCA
GCC
GCG
GCT
TCA
TCC
TCG
TCT
ACA
ACC
ACG
ACT
CCA
CCC
CCG
CCT
GCA
GCC
GCG
GCT
TCA
TCC
TCG
TCT
ACA
ACC
ACG
ACT
CCA
CCC
CCG
CCT
GCA
GCC
GCG
GCT
TCA
TCC
TCG
TCT
ATA
ATC
ATG
ATT
CTA
CTC
CTG
CTT
GTA
GTC
GTG
GTT
TTA
TTC
TTG
TTT
ATA
ATC
ATG
ATT
CTA
CTC
CTG
CTT
GTA
GTC
GTG
GTT
TTA
TTC
TTG
TTT
ATA
ATC
ATG
ATT
CTA
CTC
CTG
CTT
GTA
GTC
GTG
GTT
TTA
TTC
TTG
TTT
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
C
T
T
T
T
T
T
T
T
T
T
T
T
T
T
T
T
T
T
T
T
T
T
T
T
T
T
T
T
T
T
T
T
T
T
T
T
T
T
T
T
T
T
T
T
T
T
T
T
23,047,274 SNVs 2,349,101 SNVs
30,0000 0
15,0000
50000
10,0000
10000
10,0000
A1 1,081,955 SNVs
A2 524,139 SNVs
112,093 SNVs
Non-private post-divergence mutations
287,680 SNVs
18,339 SNVs
324,895 SNVs
Private mutationsPre-divergence mutations (A1/A2)
CedBTN1CedBTN2
Germline signatures
BTN-specific signatures
0.10
0.05
0
0.050
Mut. probability
0.050
0.050
Mut. probability
SBS-A SBS-B SBS-C
SBS-D SBS-E
A
B
C
D
E
1
2
3
4
5
6+
1
2
3
4
5
6+
0
1
2
3
4
5+
0
1
2
3
4
5+
1
2
3
4
5
6+
1
2
3
4
5
6+
1
2
3
4
5
6+
1
2
3
4
5
6+
0
1
2
3
4
5+
0
1
2
3
4
5+
0
1
2
3
4
5+
0
1
2
3
4
5+
1
1
2
1
2
3
1
2
3
4
5+
Homopolymer length Homopolymer length Number of repeat units Number of repeat units
Microhomology length
15000
Microhomology
(deletion length)
TC CT
1-bp deletion 1-bp insertion >1-bp deletion at repeat
(deletion length) >1-bp insertion at repeat
(insertion length)
2 3 4 5+ 2 3 4 5+ 2 3 4 5+
1
2
3
4
5
6+
1
2
3
4
5
6+
0
1
2
3
4
5+
0
1
2
3
4
5+
1
2
3
4
5
6+
1
2
3
4
5
6+
1
2
3
4
5
6+
1
2
3
4
5
6+
0
1
2
3
4
5+
0
1
2
3
4
5+
0
1
2
3
4
5+
0
1
2
3
4
5+
1
1
2
1
2
3
1
2
3
4
5+
Mutations
Homopolymer length Homopolymer length Number of repeat units Number of repeat units Microhomology length
400,0000
Microhomology
(deletion length)
TC CT
1-bp deletion 1-bp insertion >1-bp deletion at repeat
(deletion length) >1-bp insertion at repeat
(insertion length)
2 3 4 5+ 2 3 4 5+ 2 3 4 5+
Healthy (3 samples) CedBTN (10 samples, excluding A0)
4,590,678 indels 22,568 indels
SBS-A
SBS-B
SBS-C
SBS-D
SBS-E
Ancestral to
CedBTN1 & CedBTN2 (A0)
CedBTN1: Pre-divergence (A1)
Non-private post-divergence
CedBTN2: Pre-divergence (A2)
Private (7 samples)
Non-private post-divergence Private (3 samples)
Healthy (3 samples)
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12
BTN-specific indels present lower contributions from ID1 and ID2 relative to the germ line, and seem
enriched in ID5 (single-nucleotide deletions at A/T homopolymers, of unknown aetiology) and ID8
(long insertions and deletions, possibly caused by repair of DNA double-strand breaks via non-
homologous end-joining (29)). Hence, mutational processes absent from the germ line, and possibly
linked to genomic instability, appear to have contributed substantial fractions of indels to CedBTN
genomes.
Pervasive genomic instability drives the evolution of cockle BTN
Previous cellular studies have shown that cockle DN is distinguished by an unusual, broad continuum
of ploidy ranging from 1.3n to 9.6n, and a variable karyotype marked by abundant microchromosomes
(39–41). To further investigate this hallmark of DN in cockle BTN, we performed cytogenetic analysis
of 261 metaphase spreads from neoplastic cells in six tumours, three from each CedBTN lineage (Fig.
S15). This revealed extensive variation in chromosome number and size across tumours, with the
median chromosome number per sample varying between 98 and 276 (Table S12). Notably, we also
observed wide variability in chromosome number within individual tumours. For instance, neoplastic
metaphase spreads from sample PACE17/478H contained 11–354 chromosomes of variable size and
structure. Fluorescent in situ hybridization (FISH) probes targeting telomeric sequences showed that,
despite such karyotypic plasticity, all the chromosomes in CedBTN cells present a canonical structure
(Fig. 4A). These results suggest that the shifting karyotypes of CedBTN are probably the outcome of
extensive chromosomal reorganization and frequent chromosome mis-segregation during anaphase. It
therefore seems likely that a fraction of cell divisions may produce inviable cells in these tumours.
Next, we inferred copy number (CN) profiles from whole-genome sequencing data for each tumour in
our ‘golden set’. The profiles were marked by a ubiquitous pattern of highly complex CN alterations
along every reference chromosome, with lower CN levels visibly underrepresented (Fig. 4B). CN
distributions were consistent with a modal CN of 4n, suggestive of ancestral tetraploidy, except for one
tumour (UGCE17/2401H) presenting a modal CN of 5n. Profiles were loosely conserved across
tumours from each lineage, with a combination of shared and sample-specific CN features (Fig. S16).
Moreover, CN distributions revealed a strong aberrant background of chromosomal regions with
additional CN states, which in some cases obscured the expected tetramodal or pentamodal CN profile
(Fig. S16). The cytogenetic findings above suggest that this aberrant CN background may result from
persistent chromosome mis-segregation, possibly resulting in intra-tumour heterogeneity in CN. Such
heterogeneity is probably amplified by cell transmission bottlenecks to produce the observed inter-
tumour CN variability. Overall, our analyses indicate that both CedBTN clones are highly aneuploid,
polyploid lineages that suffered at least one whole-genome duplication event in early tumorigenesis,
leading to a likely tetraploid state that, in the case of CedBTN2, later developed further CN gains in the
UGCE17/2401H branch.
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13
Figure 4. Chromosomal, copy number and structural variation in cockle BTN. A, FISH of telomeric peptide
nucleic acid probes (TEL, shown in green) onto healthy (left) and representative type A (centre) and type B
neoplastic metaphase spreads. All chromosomes, including the smallest neoplastic chromosomes, hold telomeric
signals on all chromatid ends. Scale bars, 10 µm. B, CN profiles of representative healthy, CedBTN1 and
CedBTN2 samples. Grey dots represent estimates of unrounded CN for 10-kb windows along the reference
genome (x-axis); blue segments indicate inferred segments of integer CN. Distributions of unrounded CN are
shown on the right margin. C, Phylogenetic tree inferred from BTN-specific SVs. The number of SVs per branch
is indicated, and branches corresponding to sets of ancestral or pre-divergence variants (A0, A1, A2) are labelled.
Bootstrap support values (n=1000 replicates) are ≥99.9 for all nodes except that marked with symbol Ä (91.6). D,
Copy number profiles in a 500-kb region around the MGMT gene locus in healthy (n=3) and CedBTN1 (n=7)
samples. Each sample is represented by a line. The highest CedBTN1 CN estimate at the gene locus (CN=0.4)
corresponds to sample EICE18/889H. E, Numbers of sequence reads aligning to five satellite DNA elements
identified in a diverse set of healthy cockles (n=30) and CedBTN1 (n=7) and CedBTN2 (n=3) tumours. Each dot
represents a sample. Boxes represent first and third quartiles; middle line within each box denotes the median;
whiskers indicate values within 1.5× interquartile range from the first and third quartiles. Monomer size is
provided for each satellite. F, FISH of DNA probe for satellite CeS4 (red) onto representative metaphases of
healthy (left) and neoplastic specimens. Scale bars, 10 µm; DAPI, 4′,6-diamidino-2-phenylindole.
A
C
D
E
B
F
CedBTN1
(FRCE17/701H)
Copy number
0
4
8
6
2
10
CedBTN2 (UGCE17/2401H)
Copy number
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
0
4
8
6
2
10
Healthy (ICCE19/431F)
Copy number
0
4
6
2
0 5000 10,000 15,000 20,000
Reads per sample
CeS4 (382 bp) CeS14 (1900 bp) CeS6 (435 bp) CeS31 (4244 bp) CeS17 (2950 bp)
CedBTN1
CedBTN2
Healthy
CeS4 CeS4
582
409
103
51
128
37
26
40
30
351
84
77
3093
2208
1153
1032
CedBTN1
CedBTN2
2825
(A1)
2582
(A2)
76
(A0)
EICE18/887H
EPCE18/848H
UGCE17/2401H
EICE18/889H
EUCE18/1024H
PVCE17/1247H
PVCE17/1402H
FRCE17/701H
PACE17/433H
PACE17/421H1
Chromosome 3 position
Copy number
0
2
4
6
MGMT
Healthy
(3 samples)
MGMT
CedBTN1 (7 samples)
Copy number
0
2
4
6
1,400,000 1,500,000 1,600,000 1,700,000
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14
To further characterize the landscape of somatic alterations in cockle BTN, we applied multiple
established algorithms to call structural variants in the 10 ‘golden set’ tumours. We then removed
potentially germline events by genotyping these variants on 455 non-neoplastic samples. This approach
yielded a conservative set 18,272 high-confidence structural variants (6,916 in CedBTN1, 10,925 in
CedBTN2), with deletions being the most frequent type of event (80%, 14,589/18,272; Fig. S17). A
maximum-parsimony phylogenetic tree reconstructed from these variants confirmed the CedBTN
nuclear phylogeny inferred from SNVs, supporting two divergent lineages with a minimal fraction of
shared structural variants (Fig. 4C).
Although analysis of dN/dS ratios revealed no evidence of positive selection for post-divergence SNVs
or indels in either clone, the availability of CN data offered an additional opportunity to identify
potential early cancer-driver alterations. We systematically screened for gains (CN³8) and losses
(CN£1) of regions containing oncogenes and tumour suppressor genes, respectively. This analysis
detected likely ancestral amplification of two canonical oncogenes in CedBTN1: MDM2 (10–13 copies
in CedBTN1; mean CN=10.9; gene CN percentile=98.3), encoding an important inhibitor of tumour
suppressor proteins, and CCND3 (8–18 copies in CedBTN1; mean CN=10.7; gene CN percentile=98.2),
encoding a cyclin that promotes the G1/S cell cycle transition (Table S13). Recurrent amplification of
these genes has been observed in multiple cancer types, and is thought to prevent cell cycle arrest and
apoptosis under conditions of genomic instability (42–45). Notably, we also identified an ancestral
homozygous deletion of MGMT in CedBTN1 (Fig. 4D; Table S13). The enzyme encoded by this gene,
O6-methylguanine-DNA methyltransferase, is essential for repair of alkylated DNA bases, and its
inactivation results in hypersensitivity to the toxic and mutagenic effects of alkylating agents (46–48).
Given the cumulative and virtually lineage-specific activity of signature SBS-D (Fig. 3D), and its
similarity to COSMIC SBS11 (caused by the alkylating agent temozolomide (32)), SBS-D most likely
reflects unrepaired alkylation of DNA bases due to loss of MGMT. The resemblance between SBS-D
and SBS23 further suggests that SBS23 may arise from deficient DNA alkylation repair in human
cancers.
Satellite DNA expansions illuminate the emergence of CedBTN
Finally, we applied a computational method to examine the repetitive complement of the C. edule
genome, with a focus on satellite DNA. These repetitive sequences are relevant for genome stability,
exhibiting long-term conservation and propensity for rapid copy number changes (49). Our method
identified 34 satellite DNA candidates in the common cockle reference genome (Table S14), four of
which varied in frequency between non-neoplastic and BTN genomes, providing further insights into
the origins of cockle BTN (Fig. 4E). Two satellites, named CeS4 and CeS14, were found at high
frequency in all samples from a genetically diverse cohort of non-neoplastic cockles, yet were entirely
absent from both BTN clones. We designed FISH probes to target satellite CeS4, which confirmed the
results obtained from sequencing data (Fig. 4F). This finding suggests that both CedBTN1 and
CedBTN2 may be ancient cancer lineages that diverged from the cockle population before the
emergence and expansion of CeS4 and CeS14 in the C. edule germ line. Another satellite, CeS6, was
found in cockle populations and CedBTN2 samples, while being absent from CedBTN1 (Fig. 4E).
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15
Lastly, despite satellite CeS31 being exclusive to CedBTN1, our data did not support exclusive presence
of any satellite DNA in CedBTN2 samples. These observations suggest that CedBTN2 may have
diverged from the cockle population more recently than CedBTN1.
Discussion
Despite several BTN clones having been newly described in recent years (9–14), no analyses of whole
BTN genomes have yet been reported. Combining a range of approaches, our study provides a first
outlook into the genomes of these singular marine leukaemias in European common cockles,
complementing the work of Hart et al. (30) on American soft-shell clams. Both studies reveal neoplastic
genomes marked by structural instability. In the case of cockle BTN, we find evidence for ongoing
extreme genomic instability, most likely activated by early whole-genome duplication (50) and fuelled
by recurrent chromosome mis-segregation during mitosis (51). This is in stark contrast with the three
transmissible cancers described in terrestrial mammals (dogs and Tasmanian devils), which present
remarkable karyotypic stability (1, 5, 52), and thus challenges the notion that development of a durable
genome architecture is required for long-term survival of cancer lineages. Although our data do not
allow estimation of precise ages for cockle BTN, multiple lines of evidence suggest that these clones
may have emerged centuries or millennia ago. These include the broad geographic distribution of
tumours, the marked genetic divergence between tumours and modern cockles, the recurrent capture of
host mitochondria by tumours, and the absence in tumours of satellite DNA elements that are vastly
expanded in the cockle germ line. Furthermore, Hart et al. estimate an age of ~500 years for the BTN
clone affecting soft-shell clams (30), supporting that long-term survival of marine transmissible cancers
is possible. Taken together, our findings suggest that CedBTN lineages have undergone a relatively
long history of pervasive genomic instability. Studying the mechanisms that enable BTN cells to
overcome the effects of such instability will broaden our understanding of the conditions required for
cancers to survive and adapt over the long term.
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Acknowledgements
We thank the fishermen’s associations (‘cofradías’) of Galicia for their advice and assistance with sampling, and
the Galicia Supercomputing Centre (CESGA) for the availability of informatic resources. We thank L.F. Møller
(National Institute of Aquatic Resources, Denmark), B. Hussel (Alfred Wegener Institute), M. Wolowicz
(University of Gdansk), T. Verstraeten (Ghent University), M.L. Martínez and A.M. Insua Pombo (Universidade
.CC-BY 4.0 International licensemade available under a
(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is
The copyright holder for this preprintthis version posted August 7, 2022. ; https://doi.org/10.1101/2022.08.06.503021doi: bioRxiv preprint
18
da Coruña), C. García de Leaniz (Swansea University), A. Smith and A. Harvey (Marine Biological Association,
UK), R. Parks (Centre for Environment, Fisheries and Aquaculture Science, UK) and T. Magnesen (Universitetet
i Bergen) for providing samples for this project. We thank C. Canchaya (Universidade de Vigo), M. Rey, J.
Quinteiro, M. Hermida and P. Martínez (Universidade de Santiago de Compostela) for helpful advice on genome
assembly and annotation, M. Rodríguez (Universidade de Vigo) for administrative support, and E.P. Murchison
(University of Cambridge) for helpful advice and critical reading of the manuscript. Funding: This research was
funded by the European Research Council (ERC) Starting Grant no. 716290 (‘SCUBA CANCERS’), awarded to
J.M.C.T. Sampling research was carried out mainly at the Universidade de Vigo’s Centro de Investigación Mariña,
supported by the ‘Excellence in Research (INUGA)’ Program from the Regional Council of Culture, Education
and Universities, and co-funded by the European Union through the ERDF Operational Program Galicia 2014–
2020 ‘A way to make Europe’. Molecular biology and bioinformatics research was carried out at mainly the
Centre for Research in Molecular Medicine and Chronic Diseases (CiMUS), supported by the European Regional
Development Fund ‘A way to make Europe’ and the Research Centre of the Galician University System (2019–
2022). A.L.B. was supported by a predoctoral fellowship from the Spanish Ministry of Economy, Industry, and
Competitiveness (BES2016/078166), received funding from European Union’s Horizon 2020 research and
innovation program under grant agreement No. 730984 ASSEMBLE PLUS Transnational Access, and a travel
grant from Boehringer Ingelheim Fonds. M.Sa. was supported by a predoctoral fellowship from the Spanish
regional government of Xunta de Galicia (ED481A-2017/299). D.G.-S. was supported by postdoctoral contracts
from Xunta de Galicia (ED481B-2018/091 and ED481D 2022/001). S.D. received funding from European
Union’s Horizon 2020 research and innovation program under grant agreement No. 730984 ASSEMBLE PLUS
Transnational Access. I.O. was supported by a predoctoral fellowship from the Spanish regional government of
Xunta de Galicia Consellería de Cultura, Educación y Universidad (ED481A 2021/096). J.R.-C. was partially
supported by the program to structure and improve research centres (Centros Singulares 2019, CiMUS). T.P. was
supported by a predoctoral fellowship from the Spanish Government (FPU15/03709) and a predoctoral fellowship
from the Spanish regional government of Xunta de Galicia (ED481A-2015/083). L.T. was supported by a
predoctoral fellowship from the Spanish regional government of Xunta de Galicia (ED481A-2018/303). A.M.A.
received funding from Portuguese national funds FCT (Foundation for Science and Technology) through project
UIDB/04326/2020, UIDP/04326/2020, and LA/P/0101/2020, and from the operational programs CRESC Algarve
2020 and COMPETE 2020 through project EMBRC-PT ALG-01-0145-FEDER-022121. R.C. was supported by
FCT/MCTES (UIDP/50017/2020, UIDB/50017/2020, LA/P/0094/2020), through national Portuguese funds.
M.Sk. was supported by Russian Science Foundation, grant No 19-74-20024. N.G.P. provided biological
resources supplied by EMBRC-ERIC. K.S. was partially supported by the National Centre of Science (Poland)
within grant No UMO-2017/26/M/NZ8/00478. J.J.P. was supported by the Spanish regional government of Xunta
de Galicia (ED431C 2020/05), and Fondos Feder ‘Unha maneira de facer Europa’. Z.N. was supported by
Wellcome no. WT098051. Y.S.J. was supported by a grant from the National Research Foundation of Korea
funded by the Korean Government (NRF-2020R1A3B2078973). D.P. was supported by the Spanish Ministry of
Science and Innovation, MICINN (PID2019-106247GB-I00 awarded to D.P.), the European Research Council
(ERC-617457-PHYLOCANCER awarded to D.P.), and the Spanish regional government of Xunta de Galicia.
J.D. was supported by a postdoctoral fellowship from the Belgian Research Foundation, Flanders (FWO;
12J6921N). Author contributions: A. Villal., D.P. and J.M.C.T. designed the project. A.L.B., M.Sa., D.G.-S.,
S.D., S.R., J.Z., M.A.Q., I.O., J.J.P., J.D. and A.B.-O. developed methods. A.L.B., M.Sa., D.G.-S., S.D., S.R.,
J.Z., Y.L., I.O., J.T., Y.S.J., J.D. and A.B.-O. performed computational analyses. T.P., L.T., J.A., Z.N. and D.P.
assisted with analyses. A.L.B., M.Sa., D.G.-S., S.D., A. Villan., A.P.-V, A.V.-F., J.T., J.R.-C., P.A., J.A. and J.J.P.
performed laboratory work. A.L.B., D.G.-S., S.D., M.A.Q., A.P.-V, J.T. and J.R.-C. performed sequencing
methods. A.L.B., D.G.-S., S.D., A.V.-F., A. Villan., D.C., R.R., J.A., A.M.A, P.B., R.C., B.E.K., U.I., X.M.,
N.G.P., I.P., F.R., P.R., M.Sk. and K.S. provided samples. A.L.B., M.Sa., D.G.-S., S.D., S.R., J.Z., Y.L., J.J.P.,
Y.S.J., D.P., J.D., A.B.-O. helped with interpretation of results. A.L.B., D.G.-S., S.D., A.P.-V, J.R.-C., A. Villan.,
P.A., J.A. performed sample management. A.C., D.I., M.J.C, A. Villal., Z.N. and D.P. provided technical advice.
A.L.B., M.Sa., D.G.-S., S.D. Y.L., J.Z., J.D. and A.B.-O. generated figures. A.B.-O. and J.M.C.T. wrote the
manuscript with contributions from all other authors. Competing interests: The authors declare no competing
interests.
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(which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is
The copyright holder for this preprintthis version posted August 7, 2022. ; https://doi.org/10.1101/2022.08.06.503021doi: bioRxiv preprint
