Joint copy number and mutation phylogeny reconstruction from single-cell amplicon sequencing data

Reconstructing the history of somatic DNA alterations that occurred in a tumour can help understand its evolution and predict its resistance to treatment. Single-cell DNA sequencing (scDNAseq) can be used to investigate clonal heterogeneity and to inform phylogeny reconstruction. However, existing phylogenetic methods for scDNAseq data are designed either for point mutations or for large copy number variations, but not for both types of events simultaneously. Here, we develop COMPASS, a computational method for inferring the joint phylogeny of mutations and copy number alterations from targeted scDNAseq data. We evaluate COMPASS on simulated data and show that it outperforms existing methods. We apply COMPASS to a large cohort of 123 patients with acute myeloid leukemia (AML) and detect copy number alterations, including subclonal ones, which are in agreement with current knowledge of AML development. We further used bulk SNP array data to orthogonally validate or findings.

Sensitivity of A Frequency-Based Alignment-Free Approach For Phylogeny Rreconstruction.

Background: Phylogenies enrich our understanding of how genes, genomes, and species evolve. Traditionally, alignment-based methods are used to construct phylogenies from genetic sequence data; however, this process can be time-consuming when analyzing the large amounts of genomic data available today. Additionally, these analyses face challenges due to differences in genome structure, synteny, and the need to identify similarities in the face of repeated substitutions resulting in loss of phylogenetic information contained in the sequence. Alignment Free (AF) approaches using k-mers (short subsequences) can be an efficient alternative due to their indifference to positional rearrangements in a sequence. However, these approaches may be sensitive to k-mer length and the distance between samples.Results: In this paper, we analyzed the sensitivity of an AF approach based on k-mer frequencies to these challenges using cosine and Euclidean distance metrics for both assembled genomes and unassembled sequencing reads. Quantification of the sensitivity of this AF approach for phylogeny reconstruction to branch length and k-mer length provides a better understanding of the necessary parameter ranges for accurate phylogeny reconstruction. Our results show that a frequency-based AF approach can result in accurate phylogeny reconstruction when using whole genomes, but not stochastically sequenced reads, so long as longer k-mers are used. Conclusions: In this study, we have shown an AF approach for phylogeny reconstruction is robust in analyzing assembled genome data for a range of numbers of substitutions using longer k-mers. Using simulated reads randomly selected from the genome by the Illumina sequencer had a detrimental effect on phylogeny estimation. Additionally, filtering out infrequent k-mers improved the computational efficiency of the method while preserving the accuracy of the results thus suggesting the feasibility of using only a subset of data to improve computational efficiency in cases where large sets of genome-scale data are analyzed.

Comparing the topology of phylogenetic network generators

Phylogenetic networks represent evolutionary history of species and can record natural reticulate evolutionary processes such as horizontal gene transfer and gene recombination. This makes phylogenetic networks a more comprehensive representation of evolutionary history compared to phylogenetic trees. Stochastic processes for generating random trees or networks are important tools in evolutionary analysis, especially in phylogeny reconstruction where they can be utilized for validation or serve as priors for Bayesian methods. However, as more network generators are developed, there is a lack of discussion or comparison for different generators. To bridge this gap, we compare a set of phylogenetic network generators by profiling topological summary statistics of the generated networks over the number of reticulations and comparing the topological profiles.

An Information-Entropy Position-Weighted K-Mer Relative Measure for Whole Genome Phylogeny Reconstruction

Alignment methods have faced disadvantages in sequence comparison and phylogeny reconstruction due to their high computational costs in handling time and space complexity. On the other hand, alignment-free methods incur low computational costs and have recently gained popularity in the field of bioinformatics. Here we propose a new alignment-free method for phylogenetic tree reconstruction based on whole genome sequences. A key component is a measure called information-entropy position-weighted k-mer relative measure (IEPWRMkmer), which combines the position-weighted measure of k-mers proposed by our group and the information entropy of frequency of k-mers. The Manhattan distance is used to calculate the pairwise distance between species. Finally, we use the Neighbor-Joining method to construct the phylogenetic tree. To evaluate the performance of this method, we perform phylogenetic analysis on two datasets used by other researchers. The results demonstrate that the IEPWRMkmer method is efficient and reliable. The source codes of our method are provided at https://github.com/ wuyaoqun37/IEPWRMkmer.

Mitochondrial Genomes, Phylogenetic Associations, and SNP Recovery for the Key Invasive Ponto-Caspian Amphipods in Europe

The Ponto-Caspian region is the main donor of invasive amphipods to freshwater ecosystems, with at least 13 species successfully established in European inland waters. Dikerogammarus spp. and Pontogammarus robustoides are among the most successful, due to their strong invasive impact on local biota. However, genomic knowledge about these invaders is scarce, while phylogeography and population genetics have been based on short fragments of mitochondrial markers or nuclear microsatellites. In this study, we provide: (i) a reconstruction of six mitogenomes for four invasive gammarids (D. villosus, D. haemobaphes, D. bispinosus, and P. robustoides); (ii) a comparison between the structure of the newly obtained mitogenomes and those from the literature; (iii) SNP calling rates for individual D. villosus and D. haemobaphes from different invasion sites across Europe; and (iv) the first time-calibrated full mitogenome phylogeny reconstruction of several Ponto-Caspian taxa. We found that, in comparison to other gammarids, the mitogenomes of Ponto-Caspian species show a translocation between the tRNA-E and tRNA-R positions. Phylogenetic reconstruction using the mitogenomes identified that Ponto-Caspian gammarids form a well-supported group that originated in the Miocene. Our study supports paraphyly in the family Gammaridae. These provided mitogenomes will serve as vital genetic resources for the development of new markers for PCR-based identification methods and demographic studies.

Accounting for the Biological Complexity of Pathogenic Fungi in Phylogenetic Dating

In the study of pathogen evolution, temporal dating of phylogenies provides information on when species and lineages may have diverged in the past. When combined with spatial and epidemiological data in phylodynamic models, these dated phylogenies can also help infer where and when outbreaks occurred, how pathogens may have spread to new geographic locations and/or niches, and how virulence or drug resistance has developed over time. Although widely applied to viruses and, increasingly, to bacterial pathogen outbreaks, phylogenetic dating is yet to be widely used in the study of pathogenic fungi. Fungi are complex organisms with several biological processes that could present issues with appropriate inference of phylogenies, clock rates, and divergence times, including high levels of recombination and slower mutation rates although with potentially high levels of mutation rate variation. Here, we discuss some of the key methodological challenges in accurate phylogeny reconstruction for fungi in the context of the temporal analyses conducted to date and make recommendations for future dating studies to aid development of a best practices roadmap in light of the increasing threat of fungal outbreaks and antifungal drug resistance worldwide.

Two new species of the Balkan genus Paladilhiopsis Pavlović, 1913 (Caenogastropoda, Moitessieriidae)

The Balkan Peninsula is inhabited by the worldwide most diverse subterranean gastropod fauna. This fauna is still poorly studied, since its habitats are not easily accessible, and its sampled populations are mostly not rich in specimens’ numbers. Often only empty shells are known, but the shell is hardly useful, not only in phylogeny reconstruction, but even in species determination. The exclusively obligatory subterranean family Moitessieriidae is especially poorly studied. Representatives of the genus Paladilhiopsis Pavlović, 1913 (Moitessieriidae) collected at three localities, distributed in Croatia and Bosnia & Herzegovina, were studied. The pigmentation of their shells and soft parts, as well as the female and male reproductive organs in one taxon, are presented. The partial sequences of the molecular markers mitochondrial cytochrome oxidase subunit I (COI) and nuclear histone 3 (H3) were used to infer their systematic status and phylogenetic relationships. Two species new to science are described. For one of them, also studied anatomically, 15 specimens were sequenced for COI, and all show the same haplotype.

Profiles of expressed mutations in single cells reveal patterns of tumor evolution and therapeutic impact of intratumor heterogeneity

Advances in single cell RNA sequencing (scRNAseq) technologies uncovered an unexpected complexity in solid tumors, underlining the relevance of intratumor heterogeneity for cancer progression and therapeutic resistance. Heterogeneity in the mutational composition of cancer cells is well captured by tumor phylogenies, which demonstrate how distinct cell populations evolve, and, e.g. develop metastatic potential or resistance to specific treatments. Unfortunately, because of their low read coverage per cell, mutation calls that can be made from scRNAseq data are very sparse and noisy. Additionally, available tumor phylogeny reconstruction methods cannot computationally handle a large number of cells and mutations present in typical scRNAseq datasets. Finally, there are no principled methods to assess distinct subclones observed in inferred tumor phylogenies and the genomic alterations that seed them. Here we present Trisicell, a computational toolkit for scalable tumor phylogeny reconstruction and evaluation from scRNAseq as well as single cell genome or exome sequencing data. Trisicell allows the identification of reliable subtrees of a tumor phylogeny, offering the ability to focus on the most important subclones and the genomic alterations that are associated with subclonal proliferation. We comprehensively assessed Trisicell on a melanoma model by comparing the phylogeny it builds using scRNAseq data, to those using matching bulk whole exome (bWES) and transcriptome (bWTS) sequencing data from clonal sublines derived from single cells. Our results demonstrate that tumor phylogenies based on mutation calls from scRNAseq data can be robustly inferred and evaluated by Trisicell. We also applied Trisicell to reconstruct and evaluate the phylogeny it builds using scRNAseq data from melanomas of the same mouse model after treatment with immune checkpoint blockade (ICB). After integratively analyzing our cell-specific mutation calls with their expression profiles, we observed that each subclone with a distinct set of novel somatic mutations is strongly associated with a distinct developmental status. Moreover, each subclone had developed a specific ICB-resistance mechanism. These results demonstrate that Trisicell can robustly utilize scRNAseq data to delineate intratumoral heterogeneity and tumor evolution.