Cancer Prevalence Across Vertebrates

Cancer is pervasive across multicellular species, but what explains differences in cancer prevalence across species? Using 16,049 necropsy records for 292 species spanning three clades (amphibians, sauropsids and mammals) we found that neoplasia and malignancy prevalence increases with adult weight (contrary to Petos Paradox) and somatic mutation rate, but decreases with gestation time. Evolution of cancer susceptibility appears to have undergone sudden shifts followed by stabilizing selection. Outliers for neoplasia prevalence include the common porpoise (<1.3%), the Rodrigues fruit bat (<1.6%) the black-footed penguin (<0.4%), ferrets (63%) and opossums (35%). Discovering why some species have particularly high or low levels of cancer may lead to a better understanding of cancer syndromes and novel strategies for the management and prevention of cancer.

Stronger Together: Cancer Clones Cooperate to Alleviate Growth Barriers in Critical Cancer Progression Transitions

Hershey and colleagues recently showed how clones in a triple-negative breast cancer cell line cooperate for their mutual fitness benefit. In this system, clones exchange soluble metabolites to increase their in vitro growth rate at low population densities, therefore mitigating the documented growth barrier that reduces individual fitness in small tumor cell populations (Allee effect). Such cooperation could aid important transitions in cancer progression in which cancer cell populations are small, like invasion or metastasis. Using orthotopic transplantation, the authors demonstrate that this cooperation is functional in one such transition in vivo, increasing the metastatic load and number of metastases, which are usually polyclonal. Together, these findings highlight the need to consider ecologic interactions to properly understand tumor growth dynamics, and how they complement the standing evolutionary model of cancer progression in our quest to understand and treat cancer.

Growth Dynamics of Ductal Carcinoma in Situ Recapitulate Normal Breast Development

Ductal carcinoma in situ (DCIS) and invasive breast cancer share many morphologic, proteomic, and genomic alterations. Yet in contrast to invasive cancer, many DCIS tumors do not progress and may remain indolent over decades. To better understand the heterogenous nature of this disease, we reconstructed the growth dynamics of 18 DCIS tumors based on the geo-spatial distribution of their somatic mutations. The somatic mutation topographies revealed that DCIS is multiclonal and consists of spatially discontinuous subclonal lesions. Here we show that this pattern of spread is consistent with a new 'Comet' model of DCIS tumorigenesis, whereby multiple subclones arise early and nucleate the buds of the growing tumor. The discontinuous, multiclonal growth of the Comet model is analogous to the branching morphogenesis of normal breast development that governs the rapid expansion of the mammary epithelium during puberty. The branching morphogenesis-like dynamics of the proposed Comet model diverges from the canonical model of clonal evolution, and better explains observed genomic spatial data. Importantly, the Comet model allows for the clinically relevant scenario of extensive DCIS spread, without being subjected to the selective pressures of subclone competition that promote the emergence of increasingly invasive phenotypes. As such, the normal cell movement inferred during DCIS growth provides a new explanation for the limited risk of progression in DCIS and adds biologic rationale for ongoing clinical efforts to reduce DCIS overtreatment.

Cancer Prevalence Across Vertebrates

Cancer is pervasive across multicellular species, but what explains differences in cancer prevalence across species? Using 16,049 necropsy records for 292 species spanning three clades (amphibians, sauropsids and mammals) we found that neoplasia and malignancy prevalence increases with adult weight (contrary to Peto's Paradox) and somatic mutation rate, but decreases with gestation time. Evolution of cancer susceptibility appears to have undergone sudden shifts followed by stabilizing selection. Outliers for neoplasia prevalence include the common porpoise (<1.3%), the Rodrigues fruit bat (<1.6%) the black-footed penguin (<0.4%), ferrets (63%) and opossums (35%). Discovering why some species have particularly high or low levels of cancer may lead to a better understanding of cancer syndromes and novel strategies for the management and prevention of cancer.

Abstract PD2-09: Characterization of the lymphovascular invasion microenvironment reveals immune response dichotomy

Background: Metastasis is the leading cause of cancer related deaths in breast cancer patients. Lymphovascular invasion represents one of the earliest stages of metastasis wherein the cells are introduced to a very different and distinct microenvironment. Methods: We leveraged spatial techniques developed for limited specimens in archival tissue to study patient matched cross-sectional tumor samples from different stages of breast neoplasia including normal breast, ductal carcinoma in situ (DCIS), primary invasive carcinoma (IBC), lymphovascular invasion (LVI) and regional lymph node metastasis. We selected a set of 21 patients with ER+ breast cancer to generate cross-sectional samples of each of these stages, for a total of 331 samples. The areas of LVI were identified by a combination of H&E review and immunohistochemistry for podoplanin. We performed smart-3SEQ for gene expression profiling and light pass whole genome sequencing for DNA copy number alterations. Results: We profiled the spectrum of neoplasia for transcriptome-wide gene expression. Principal component analysis of all 252 DCIS, LVI, IBC, or metastasis samples using the top 500 genes with the highest variance demonstrated that clustering was roughly based on the diagnostic stage (i.e. DCIS, LVI, IBC, or metastasis). Differential gene expression profiling identified thousands of genes increased or decreased in expression across the transitional stages with the largest change in gene expression being the transition from normal breast to DCIS, dominated by gene expression down regulation. We next performed NMF clustering on 62 samples of LVI from 18 cases and identified two patterns of gene expression which define two subgroups. Gene ontology analysis revealed that one cluster was associated with increased proliferation and metabolism, whereas the second cluster was dominated by an immune response. When we analyzed the immune and proliferative LVI subgroups separately, we found that the immune profiles in the patient matched IBC and LVI samples from the LVI Immune cluster were similar, whereas the immune profiles in the patient matched IBC and LVI samples from the Proliferative cluster were significantly different. At the LVI stage, all immune cell populations estimated by CibersortX were decreased in the Proliferative LVI cluster. These changes were validated using immunofluorescence for proliferation (Ki67), T cells (CD3) and macrophages (CD68) on the same samples. Using the LVI centroids, we built a model that could predict the same clusters in the METABRIC IBC. Kaplan-Meier analysis showed a significant difference between groups, with the Proliferative-like IBC group having a worse prognosis than the Immune-like IBC group. Conclusions: We observed a dichotomy at the LVI stage with a more proliferative cluster that may escape the immune response and an immune cluster which has a microenvironment with a similar pattern to its primary IBC. The recognition of two groups of LVI, differing in immune association and proliferation, raises the possibility that the risk of metastasis could be different in these two groups, leading to different biological pathways of progression.

Citation Format: Belén Rivero-Gutiérrez, Diego Mallo, Almudena Espín-Pérez, Sujay Vennam, Chunfang Zhu, Sushama Varma, Greg Scott, Joseph Foley, E Shelley Hwang, Carlo Maley, Robert West. Characterization of the lymphovascular invasion microenvironment reveals immune response dichotomy [abstract]. In: Proceedings of the 2022 San Antonio Breast Cancer Symposium; 2022 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2023;83(5 Suppl):Abstract nr PD2-09.

Genomic analysis defines clonal relationships of ductal carcinoma in situ and recurrent invasive breast cancer

Ductal carcinoma in situ (DCIS) is the most common form of preinvasive breast cancer and, despite treatment, a small fraction (5-10%) of DCIS patients develop subsequent invasive disease. A fundamental biologic question is whether the invasive disease arises from tumor cells in the initial DCIS or represents new unrelated disease. To address this question, we performed genomic analyses on the initial DCIS lesion and paired invasive recurrent tumors in 95 patients together with single-cell DNA sequencing in a subset of cases. Our data show that in 75% of cases the invasive recurrence was clonally related to the initial DCIS, suggesting that tumor cells were not eliminated during the initial treatment. Surprisingly, however, 18% were clonally unrelated to the DCIS, representing new independent lineages and 7% of cases were ambiguous. This knowledge is essential for accurate risk evaluation of DCIS, treatment de-escalation strategies and the identification of predictive biomarkers.

A new method to accurately identify single nucleotide variants using small FFPE breast samples

Most tissue collections of neoplasms are composed of formalin-fixed and paraffin-embedded (FFPE) excised tumor samples used for routine diagnostics. DNA sequencing is becoming increasingly important in cancer research and clinical management; however it is difficult to accurately sequence DNA from FFPE samples. We developed and validated a new bioinformatic pipeline to use existing variant-calling strategies to robustly identify somatic single nucleotide variants (SNVs) from whole exome sequencing using small amounts of DNA extracted from archival FFPE samples of breast cancers. We optimized this strategy using 28 pairs of technical replicates. After optimization, the mean similarity between replicates increased 5-fold, reaching 88% (range 0-100%), with a mean of 21.4 SNVs (range 1-68) per sample, representing a markedly superior performance to existing tools. We found that the SNV-identification accuracy declined when there was less than 40 ng of DNA available and that insertion-deletion variant calls are less reliable than single base substitutions. As the first application of the new algorithm, we compared samples of ductal carcinoma in situ of the breast to their adjacent invasive ductal carcinoma samples. We observed an increased number of mutations (paired-samples sign test, P < 0.05), and a higher genetic divergence in the invasive samples (paired-samples sign test, P < 0.01). Our method provides a significant improvement in detecting SNVs in FFPE samples over previous approaches.

Abstract PR02: Inferring the evolutionary dynamics of ductal carcinoma in situ through multi-regional sequencing and mathematical modeling

Introduction. The natural history of preinvasive breast cancer, or ductal carcinoma in situ (DCIS) remains poorly understood. Overcoming this gap would allow risk-appropriate treatment for patients diagnosed with DCIS. We used a multiregional sequencing approach in combination with mathematical modeling to characterize the evolutionary dynamics of DCIS initiation and progression. Methods. We analyzed a cohort of 18 patients diagnosed with DCIS, either with (n=9) or without (n=9) synchronous invasive cancer. Based on whole exome sequencing, tumor-specific mutation panels were constructed, each targeting 29-75 mutations (median: 60). From each tumor, and using selective ultraviolet radiation fractionation (SURF), we microdissected small spots (encompassing 1-3 duct cross-sections) from 3-4 spatially separated microscope sections (mean slide separation: 1.25cm, range: 0.34-6.0cm). Spots were spatially registered and genotyped based on targeted sequencing of the tumor-specific mutation panels. For each tumor, we performed unsupervised clonal deconvolution of the spot genotypes (CloneFinder) and constructed phylogenetic subclone trees. To quantify the spatial patterns of subclonal mutations, we introduced a dispersion index (DI), ranging from low (DI=0%) to high (DI=100%). To provide a spatio-temporal context for the heterogeneity patterns we developed a family of stochastic mathematical models of DCIS initiation and progression. Thereby, we embedded the evolutionary dynamics of tumor cell expansion in the branching topology of mammary ductal trees. Results. A total of 485 microdissected spots (median per tumor: 23, range: 10-50) were spatially registered and sequenced (median depth: 9,000x). All tumors were multiclonal, containing a median of 5 subclones (range: 2-14). Surprisingly, the correlation between spatial and genomic distances of spots was low. Individual subclones were diffusely dispersed across tumors. DCIS with synchronous DCIS and invasive cancer (mixed DCIS) had a higher mutation dispersion (DI=84.7%) than those without (pure DCIS, DI=70.5%; p=0.03, Wilcoxon rank-sum test). Mixed DCIS also had a higher fraction of spots containing more than one subclone than pure DCIS (median: 30.4% vs 0%, p=0.03). Among 7 mixed DCIS with invasive spots, 5 showed evidence of multiclonal invasion, that is more than one invading subclones were found in both in situ and invasive regions of the tumor. Mathematical modeling analyses show that the observed spatial patterns of genetic heterogeneity are consistent with a single expansion of mixing subclones across the ductal tree architecture. Conclusions. Our findings provide novel insights into the early growth and invasion dynamics of DCIS lesions. Further, we identified potential evolutionary markers for the delineation between indolent (pure) and aggressive (mixed) DCIS. This constitutes an important step towards identification of patients with low-risk DCIS who could be appropriately managed with less aggressive treatment.

Citation Format: Marc D. Ryser, Inmaculada C. Sorribes, Matthew Greenwald, Ethan Wu, Allison Hall, Diego Mallo, Lorraine M. King, Timothy Hardman, Lunden Simpson, Carlo C. Maley, Jeffrey R. Marks, Darryl Shibata, E. Shelley Hwang. Inferring the evolutionary dynamics of ductal carcinoma in situ through multi-regional sequencing and mathematical modeling [abstract]. In: Proceedings of the AACR Virtual Special Conference on Tumor Heterogeneity: From Single Cells to Clinical Impact; 2020 Sep 17-18. Philadelphia (PA): AACR; Cancer Res 2020;80(21 Suppl):Abstract nr PR02.

Abstract 2502: Genetic and functional heterogeneity of DCIS as predictors of invasive cancer

Genetic diversity both between and within individual tumors constitutes a challenge to personalized cancer medicine. Intra-tumor heterogeneity provides the genetic fuel for natural selection in clonal evolution and cancer progression. Tumors with high levels of genetic heterogeneity are hypothesized to be more likely to demonstrate aggressive behavior and progress to invasion and metastasis.

We analyzed the mutational loads from separate areas of pure DCIS and compared this to genetic heterogeneity in DCIS lesions found adjacent to invasive and metastatic cancer. Two spatially distinct areas of DCIS from each case were macro-dissected and the DNA extracted from FFPE samples. To analyze the data, we developed new bioinformatics methods that allowed analysis of small amounts of degraded DNA extracted from FFPE samples across multiple regions. Our bioinformatics pipeline was optimized on a series of 28 independent technical replicates of the same DNA sample sequenced twice, as training tools to find the best filtering parameters.

Whole exome sequencing was performed on each of the two geospatially separated samples for each case. Minimum coverage for inclusion in this study was 40X over at least 50% of the exome. We used the ratio of private mutations (only in 1 area) to public (found in both areas) mutations as a measure of intra-tumor heterogeneity.

We present an approach to measure clonal heterogeneity using a bulk sequencing strategy applied to geospatially distinct foci of DCIS. We found statistically significant difference between DCIS adjacent to invasive disease and metastatic patients' genetic divergence (t-test, p=0.013). Our findings suggest that genetic and functional heterogeneity may play an important evolutionary role as a driver for invasive progression.

Citation Format: Angelo Fortunato, Diego Mallo, Lorraine King, Timothy Hardman, Allison Hall, Jeffrey R. Marks, Shelley Shelley Hwang, Carlo C. Maley. Genetic and functional heterogeneity of DCIS as predictors of invasive cancer [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 2502.

Minimal barriers to invasion during human colorectal tumor growth

Intra-tumoral heterogeneity (ITH) could represent clonal evolution where subclones with greater fitness confer more malignant phenotypes and invasion constitutes an evolutionary bottleneck. Alternatively, ITH could represent branching evolution with invasion of multiple subclones. The two models respectively predict a hierarchy of subclones arranged by phenotype, or multiple subclones with shared phenotypes. We delineate these modes of invasion by merging ancestral, topographic, and phenotypic information from 12 human colorectal tumors (11 carcinomas, 1 adenoma) obtained through saturation microdissection of 325 small tumor regions. The majority of subclones (29/46, 60%) share superficial and invasive phenotypes. Of 11 carcinomas, 9 show evidence of multiclonal invasion, and invasive and metastatic subclones arise early along the ancestral trees. Early multiclonal invasion in the majority of these tumors indicates the expansion of co-evolving subclones with similar malignant potential in absence of late bottlenecks and suggests that barriers to invasion are minimal during colorectal cancer growth.

RecPhyloXML: a format for reconciled gene trees

Motivation

A reconciliation is an annotation of the nodes of a gene tree with evolutionary events—for example, speciation, gene duplication, transfer, loss, etc.—along with a mapping onto a species tree. Many algorithms and software produce or use reconciliations but often using different reconciliation formats, regarding the type of events considered or whether the species tree is dated or not. This complicates the comparison and communication between different programs.

Results

Here, we gather a consortium of software developers in gene tree species tree reconciliation to propose and endorse a format that aims to promote an integrative—albeit flexible—specification of phylogenetic reconciliations. This format, named recPhyloXML, is accompanied by several tools such as a reconciled tree visualizer and conversion utilities.

Availability and implementation

http://phylariane.univ-lyon1.fr/recphyloxml/.

Abstract P3-07-06: Evidence for tumor heterogeneity and clonal evolution during invasive progression in breast cancer

Purpose: Intratumoral heterogeneity is well recognized to be an important driver of treatment resistance and metastasis. We undertook this N of three study to measure the degree of heterogeneity in three large preinvasive lesions, all with invasive components to determine the relationship between tumor heterogeneity, spatial distribution, clonal evolution, and invasive progression.

Methods: We identified patients A, B, C with extensive DCIS measuring 7.5 cm, 6 cm, and 7 cm associated with 0.3 cm, 3.8cm, and 3.4 cm of an invasive component and 0, 7 and 1 positive lymph node, respectively. We sequenced the tumor sample for Case A from 32 unique blocks with precise geospatial localization; invasive cancer was identified in 3 of 32 blocks. Case B had 26 blocks sequenced with invasive cancer in 13 of 26 blocks. Case C had 23 blocks sequenced with invasive in 11 of 23 blocks. For germline reference, we sequenced DNA from an uninvolved tissue from each case. NGS libraries were made from FFPE derived DNA (20-40ng) for full exome sequencing. Variant calling was performed by GATK HaplotypeCaller, Platypus and Mutect. Identified somatic mutations were annotated with Oncotator and pathway enrichment analysis was performed with Bioconductor. To investigate the clonal evolution and progression history, phylogenetic trees were constructed in R and sub-clonal analysis was performed with Treeomics.

Results: The sequence data was analyzed with Platypus, MuTect and GATK HaplotypeCaller. The somatic mutation sites were concatenated into one sequence for each sample. Both neighbor-joining trees and maximum parsimony trees were built for each case. Phylogenetic analysis and sub-clonal analysis support the multi-clonal invasion model of invasive cells, in which invasive cancer can evolve from multiple clades, either early or late in the evolutionary history, independently. Dense sampling allowed reconstruction of the temporal order of mutations that accumulated in the cell lineage of the invasive cancers. Furthermore, phylogeny and sub-clone spatial analysis revealed that distant regions may be closely genetically related and showed a weak spatial sub-clone clustering pattern, which is consistent with the predictions of Big Bang model. For driver genes, we find that except for SETD2 in Case B, the majority of driver gene mutations are sub-clonal. Somatic mutations on ATP-binding cassette (ABC) transporter pathway was found in all cases.

Conclusions: Extensive sampling and sequencing of tumors yields important insights about tumor heterogeneity and tumor progression of DCIS to invasive cancer. Variable invasive propensity was identified, with foci of invasion were geospatially associated with preinvasive regions of progressively higher mutational load.

Citation Format: Ding Y, Marks J, King L, Hardman T, Hall A, Mallo D, Rodrigo A, Maley C, Hwang S. Evidence for tumor heterogeneity and clonal evolution during invasive progression in breast cancer [abstract]. In: Proceedings of the 2018 San Antonio Breast Cancer Symposium; 2018 Dec 4-8; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2019;79(4 Suppl):Abstract nr P3-07-06.

Evolution of Barrett's esophagus through space and time at single-crypt and whole-biopsy levels

The low risk of progression of Barrett's esophagus (BE) to esophageal adenocarcinoma can lead to over-diagnosis and over-treatment of BE patients. This may be addressed through a better understanding of the dynamics surrounding BE malignant progression. Although genetic diversity has been characterized as a marker of malignant development, it is still unclear how BE arises and develops. Here we uncover the evolutionary dynamics of BE at crypt and biopsy levels in eight individuals, including four patients that experienced malignant progression. We assay eight individual crypts and the remaining epithelium by SNP array for each of 6-11 biopsies over 2 time points per patient (358 samples in total). Our results indicate that most Barrett's segments are clonal, with similar number and inferred rates of alterations observed for crypts and biopsies. Divergence correlates with geographical location, being higher near the gastro-esophageal junction. Relaxed clock analyses show that genomic instability precedes and is enhanced by genome doubling. These results shed light on the clinically relevant evolutionary dynamics of BE.

Abstract P2-05-05: Not presented

This abstract was not presented at the symposium.

Multilocus inference of species trees and DNA barcoding

The unprecedented amount of data resulting from next-generation sequencing has opened a new era in phylogenetic estimation. Although large datasets should, in theory, increase phylogenetic resolution, massive, multilocus datasets have uncovered a great deal of phylogenetic incongruence among different genomic regions, due both to stochastic error and to the action of different evolutionary process such as incomplete lineage sorting, gene duplication and loss and horizontal gene transfer. This incongruence violates one of the fundamental assumptions of the DNA barcoding approach, which assumes that gene history and species history are identical. In this review, we explain some of the most important challenges we will have to face to reconstruct the history of species, and the advantages and disadvantages of different strategies for the phylogenetic analysis of multilocus data. In particular, we describe the evolutionary events that can generate species tree—gene tree discordance, compare the most popular methods for species tree reconstruction, highlight the challenges we need to face when using them and discuss their potential utility in barcoding. Current barcoding methods sacrifice a great amount of statistical power by only considering one locus, and a transition to multilocus barcodes would not only improve current barcoding methods, but also facilitate an eventual transition to species-tree-based barcoding strategies, which could better accommodate scenarios where the barcode gap is too small or inexistent.

This article is part of the themed issue ‘From DNA barcodes to biomes’.

Abstract P1-05-30: Genomic and microenvironmental intra-tumor heterogeneity in DCIS

Intra-tumor heterogeneity drives neoplastic progression by supplying the fuel for natural selection among neoplastic cells. It also complicates screening and treatment of neoplasms. We hypothesize that the degree of intra-tumor heterogeneity in DCIS should predict which tumors are likely to become invasive and metastatic. We initiated a pilot project to test this hypothesis by comparing 9 cases of pure DCIS to 9 cases of DCIS with adjacent invasive disease. For each case, we sequenced the exome from two spatially distinct regions of DCIS as well as normal tissue taken from a lymph node with no tumor involvement. This required the development of new methods to extract high quality sequencing data from small amounts of DNA extracted from FFPE samples. We calculated the genetic divergence between the two tumor regions, defined as percent of the sequenced regions of the genome showing differences between the two samples that had sufficient sequencing coverage and quality scores for confident scoring. We also employed automated imaging analysis to score microenvironmental differences between the two tumor regions. These microenvironmental measures are based on ecological methods for measuring organismal interactions and habitats. We will present initial data on differences in phenotypic and genotypic intra-tumor heterogeneity comparing pure DCIS to DCIS associated with invasive breast cancer. Our methods can be readily translated to large tissue banks of FFPE samples from DCIS.

Citation Format: Fortunato A, King L, Mallo D, Kovacheva V, Yuan Y, Boddy A, Graham T, Aktipis A, Mardis ER, Hall A, Marks JR, Hwang S, Maley CC. Genomic and microenvironmental intra-tumor heterogeneity in DCIS [abstract]. In: Proceedings of the 2016 San Antonio Breast Cancer Symposium; 2016 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2017;77(4 Suppl):Abstract nr P1-05-30.

Natural Selection in Cancer Biology: From Molecular Snowflakes to Trait Hallmarks

Evolution by natural selection is the conceptual foundation for nearly every branch of biology and increasingly also for biomedicine and medical research. In cancer biology, evolution explains how populations of cells in tumors change over time. It is a fundamental question whether this evolutionary process is driven primarily by natural selection and adaptation or by other evolutionary processes such as founder effects and drift. In cancer biology, as in organismal evolutionary biology, there is controversy about this question and also about the use of adaptation through natural selection as a guiding framework for research. In this review, we discuss the differences and similarities between evolution among somatic cells versus evolution among organisms. We review what is known about the parameters and rate of evolution in neoplasms, as well as evidence for adaptation. We conclude that adaptation is a useful framework that accurately explains the defining characteristics of cancer. Further, convergent evolution through natural selection provides the only satisfying explanation both for how a group of diverse pathologies have enough in common to usefully share the descriptive label of "cancer" and for why this convergent condition becomes life-threatening.

A Bayesian Supertree Model for Genome-Wide Species Tree Reconstruction

Current phylogenomic data sets highlight the need for species tree methods able to deal with several sources of gene tree/species tree incongruence. At the same time, we need to make most use of all available data. Most species tree methods deal with single processes of phylogenetic discordance, namely, gene duplication and loss, incomplete lineage sorting (ILS) or horizontal gene transfer. In this manuscript, we address the problem of species tree inference from multilocus, genome-wide data sets regardless of the presence of gene duplication and loss and ILS therefore without the need to identify orthologs or to use a single individual per species. We do this by extending the idea of Maximum Likelihood (ML) supertrees to a hierarchical Bayesian model where several sources of gene tree/species tree disagreement can be accounted for in a modular manner. We implemented this model in a computer program called guenomu whose inputs are posterior distributions of unrooted gene tree topologies for multiple gene families, and whose output is the posterior distribution of rooted species tree topologies. We conducted extensive simulations to evaluate the performance of our approach in comparison with other species tree approaches able to deal with more than one leaf from the same species. Our method ranked best under simulated data sets, in spite of ignoring branch lengths, and performed well on empirical data, as well as being fast enough to analyze relatively large data sets. Our Bayesian supertree method was also very successful in obtaining better estimates of gene trees, by reducing the uncertainty in their distributions. In addition, our results show that under complex simulation scenarios, gene tree parsimony is also a competitive approach once we consider its speed, in contrast to more sophisticated models.

When (distant) relatives stay too long: implications for cancer medicine

Whole-genome analyses of human medulloblastomas show that the dominant clone at relapse is present as a rare subclone at primary diagnosis.

SimPhy: Phylogenomic Simulation of Gene, Locus, and Species Trees

We present a fast and flexible software package--SimPhy--for the simulation of multiple gene families evolving under incomplete lineage sorting, gene duplication and loss, horizontal gene transfer--all three potentially leading to species tree/gene tree discordance--and gene conversion. SimPhy implements a hierarchical phylogenetic model in which the evolution of species, locus, and gene trees is governed by global and local parameters (e.g., genome-wide, species-specific, locus-specific), that can be fixed or be sampled from a priori statistical distributions. SimPhy also incorporates comprehensive models of substitution rate variation among lineages (uncorrelated relaxed clocks) and the capability of simulating partitioned nucleotide, codon, and protein multilocus sequence alignments under a plethora of substitution models using the program INDELible. We validate SimPhy's output using theoretical expectations and other programs, and show that it scales extremely well with complex models and/or large trees, being an order of magnitude faster than the most similar program (DLCoal-Sim). In addition, we demonstrate how SimPhy can be useful to understand interactions among different evolutionary processes, conducting a simulation study to characterize the systematic overestimation of the duplication time when using standard reconciliation methods. SimPhy is available at https://github.com/adamallo/SimPhy, where users can find the source code, precompiled executables, a detailed manual and example cases.

Diversity and distribution of unicellular opisthokonts along the European coast analysed using high-throughput sequencing

The opisthokonts are one of the major super groups of eukaryotes. It comprises two major clades: (i) the Metazoa and their unicellular relatives and (ii) the Fungi and their unicellular relatives. There is, however, little knowledge of the role of opisthokont microbes in many natural environments, especially among non-metazoan and non-fungal opisthokonts. Here, we begin to address this gap by analysing high-throughput 18S rDNA and 18S rRNA sequencing data from different European coastal sites, sampled at different size fractions and depths. In particular, we analyse the diversity and abundance of choanoflagellates, filastereans, ichthyosporeans, nucleariids, corallochytreans and their related lineages. Our results show the great diversity of choanoflagellates in coastal waters as well as a relevant representation of the ichthyosporeans and the uncultured marine opisthokonts (MAOP). Furthermore, we describe a new lineage of marine fonticulids (MAFO) that appears to be abundant in sediments. Taken together, our work points to a greater potential ecological role for unicellular opisthokonts than previously appreciated in marine environments, both in water column and sediments, and also provides evidence of novel opisthokont phylogenetic lineages. This study highlights the importance of high-throughput sequencing approaches to unravel the diversity and distribution of both known and novel eukaryotic lineages.