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With rapid advancements in single-cell DNA sequencing (scDNA-seq), various computational methods have been developed to study evolution and call variants on single-cell level. However, modeling deletions remains challenging because they affect total coverage in ways that are difficult to distinguish from technical artifacts. We present DelSIEVE, a statistical method that infers cell phylogeny and single-nucleotide variants, accounting for deletions, from scDNA-seq data. DelSIEVE distinguishes deletions from mutations and artifacts, detecting more evolutionary events than previous methods. Simulations show high performance, and application to cancer samples reveals varying amounts of deletions and double mutants in different tumors.

We present SIEVE, a statistical method for the joint inference of somatic variants and cell phylogeny under the finite-sites assumption from single-cell DNA sequencing. SIEVE leverages raw read counts for all nucleotides and corrects the acquisition bias of branch lengths. In our simulations, SIEVE outperforms other methods in phylogenetic reconstruction and variant calling accuracy, especially in the inference of homozygous variants. Applying SIEVE to three datasets, one for triple-negative breast (TNBC), and two for colorectal cancer (CRC), we find that double mutant genotypes are rare in CRC but unexpectedly frequent in the TNBC samples.

Steroids are components of the eukaryotic cellular membrane and have indispensable roles in the process of eukaryotic endocytosis by regulating membrane fluidity and permeability. In particular, steroids may have been a structural prerequisite for the acquisition of mitochondria via endocytosis during eukaryogenesis. While eukaryotes are inferred to have evolved from an archaeal lineage, there is little similarity between the eukaryotic and archaeal cellular membranes. As such, the evolution of eukaryotic cellular membranes has limited our understanding of eukaryogenesis. Despite evolving from archaea, the eukaryotic cellular membrane is essentially a fatty acid bacterial-type membrane, which implies a substantial bacterial contribution to the evolution of the eukaryotic cellular membrane. Here, we address the evolution of steroid biosynthesis in eukaryotes by combining ancestral sequence reconstruction and comprehensive phylogenetic analyses of steroid biosynthesis genes. Contrary to the traditional assumption that eukaryotic steroid biosynthesis evolved within eukaryotes, most steroid biosynthesis genes are inferred to be derived from bacteria. In particular, aerobic deltaproteobacteria (myxobacteria) seem to have mediated the transfer of key genes for steroid biosynthesis to eukaryotes. Analyses of resurrected steroid biosynthesis enzymes suggest that the steroid biosynthesis pathway in early eukaryotes may have been similar to the pathway seen in modern plants and algae. These resurrected proteins also experimentally demonstrate that molecular oxygen was required to establish the modern eukaryotic cellular membrane during eukaryogenesis. Our study provides unique insight into relationships between early eukaryotes and other bacteria in addition to the well-known endosymbiosis with alphaproteobacteria.

Aneuploidy, chromosomal instability, somatic copy-number alterations, and whole-genome doubling (WGD) play key roles in cancer evolution and provide information for the complex task of phylogenetic inference. We present MEDICC2, a method for inferring evolutionary trees and WGD using haplotype-specific somatic copy-number alterations from single-cell or bulk data. MEDICC2 eschews simplifications such as the infinite sites assumption, allowing multiple mutations and parallel evolution, and does not treat adjacent loci as independent, allowing overlapping copy-number events. Using simulations and multiple data types from 2780 tumors, we use MEDICC2 to demonstrate accurate inference of phylogenies, clonal and subclonal WGD, and ancestral copy-number states.

Flavin-containing monooxygenases (FMOs) are ubiquitous in all domains of life and metabolize a myriad of xenobiotics, including toxins, pesticides and drugs. However, despite their pharmacological importance, structural information remains bereft. To further our understanding behind their biochemistry and diversity, we used ancestral-sequence reconstruction, kinetic and crystallographic techniques to scrutinize three ancient mammalian FMOs: AncFMO2, AncFMO3-6 and AncFMO5. Remarkably, all AncFMOs could be crystallized and were structurally resolved between 2.7- and 3.2-Å resolution. These crystal structures depict the unprecedented topology of mammalian FMOs. Each employs extensive membrane-binding features and intricate substrate-profiling tunnel networks through a conspicuous membrane-adhering insertion. Furthermore, a glutamate–histidine switch is speculated to induce the distinctive Baeyer–Villiger oxidation activity of FMO5. The AncFMOs exhibited catalysis akin to human FMOs and, with sequence identities between 82% and 92%, represent excellent models. Our study demonstrates the power of ancestral-sequence reconstruction as a strategy for the crystallization of proteins.Ancestral reconstruction leads to characterization and crystallization of three ancient mammalian flavin-containing monooxygenases, offering insights into their mechanisms of membrane binding, catalytic activity and substrate selection.

Abstract Nef is an accessory protein unique to the primate HIV-1, HIV-2, and SIV lentiviruses. During infection, Nef functions by interacting with multiple host proteins within infected cells to evade the immune response and enhance virion infectivity. Notably, Nef can counter immune regulators such as CD4 and MHC-I, as well as the SERINC5 restriction factor in infected cells. In this study, we generated a posterior sample of time-scaled phylogenies relating SIV and HIV Nef sequences, followed by reconstruction of ancestral sequences at the root and internal nodes of the sampled trees up to the HIV-1 Group M ancestor. Upon expression of the ancestral primate lentivirus Nef protein within CD4+ HeLa cells, flow cytometry analysis revealed that the primate lentivirus Nef ancestor robustly downregulated cell-surface SERINC5, yet only partially downregulated CD4 from the cell surface. Further analysis revealed that the Nef-mediated CD4 downregulation ability evolved gradually, while Nef-mediated SERINC5 downregulation was recovered abruptly in the HIV-1/M ancestor. Overall, this study provides a framework to reconstruct ancestral viral proteins and enable the functional characterization of these proteins to delineate how functions could have changed throughout evolutionary history.

Ancestral sequence reconstruction (ASR) is a phylogenetic method widely used to analyze the properties of ancient biomolecules and to elucidate mechanisms of molecular evolution. Despite its increasingly widespread application, the accuracy of ASR is currently unknown, as it is generally impossible to compare resurrected proteins to the true ancestors. Which evolutionary models are best for ASR? How accurate are the resulting inferences? Here we answer these questions using a cross-validation method to reconstruct each extant sequence in an alignment with ASR methodology, a method we term “extant sequence reconstruction” (ESR). We thus can evaluate the accuracy of ASR methodology by comparing ESR reconstructions to the corresponding known true sequences. We find that a common measure of the quality of a reconstructed sequence, the average probability, is indeed a good estimate of the fraction of correct amino acids when the evolutionary model is accurate or overparameterized. However, the average probability is a poor measure for comparing reconstructions from different models, because, surprisingly, a more accurate phylogenetic model often results in reconstructions with lower probability. While better (more predictive) models may produce reconstructions with lower sequence identity to the true sequences, better models nevertheless produce reconstructions that are more biophysically similar to true ancestors. In addition, we find that a large fraction of sequences sampled from the reconstruction distribution may have fewer errors than the single most probable (SMP) sequence reconstruction, despite the fact that the SMP has the lowest expected error of all possible sequences. Our results emphasize the importance of model selection for ASR and the usefulness of sampling sequence reconstructions for analyzing ancestral protein properties. ESR is a powerful method for validating the evolutionary models used for ASR and can be applied in practice to any phylogenetic analysis of real biological sequences. Most significantly, ESR uses ASR methodology to provide a general method by which the biophysical properties of resurrected proteins can be compared to the properties of the true protein.

Homogeneity across lineages is a general assumption in phylogenetics according to which nucleotide substitution rates are common to all lineages. Many phylogenetic methods relax this hypothesis but keep a simple enough model to make the process of sequence evolution more tractable. On the other hand, dealing successfully with the general case (heterogeneity of rates across lineages) is one of the key features of phylogenetic reconstruction methods based on algebraic tools. The goal of this paper is twofold. First, we present a new weighting system for quartets (ASAQ) based on algebraic and semi-algebraic tools, thus especially indicated to deal with data evolving under heterogeneous rates. This method combines the weights of two previous methods by means of a test based on the positivity of the branch lengths estimated with the paralinear distance. ASAQ is statistically consistent when applied to data generated under the general Markov model, considers rate and base composition heterogeneity among lineages and does not assume stationarity nor time-reversibility. Second, we test and compare the performance of several quartet-based methods for phylogenetic tree reconstruction (namely QFM, wQFM, quartet puzzling, weight optimization and Willson’s method) in combination with several systems of weights, including ASAQ weights and other weights based on algebraic and semi-algebraic methods or on the paralinear distance. These tests are applied to both simulated and real data and support weight optimization with ASAQ weights as a reliable and successful reconstruction method that improves upon the accuracy of global methods (such as neighbor-joining or maximum likelihood) in the presence of long branches or on mixtures of distributions on trees.

The evolutionary origins of arboviruses are unknown because their typical dual host tropism is paraphyletic within viral families. Here we studied one of the most diversified and medically relevant RNA virus families, the Bunyaviridae , in which four of five established genera are transmitted by arthropods. We define two cardinally novel bunyavirus groups based on live isolation of 26 viral strains from mosquitoes (Jonchet virus [JONV], eight strains; Ferak virus [FERV], 18 strains). Both viruses were incapable of replicating at vertebrate-typical temperatures but replicated efficiently in insect cells. Replication involved formation of virion-sense RNA (vRNA) and mRNA, including cap-snatching activity. SDS/PAGE, mass spectrometry, and Edman degradation identified translation products corresponding to virion-associated RNA-dependent RNA polymerase protein (RdRp), glycoprotein precursor protein, glycoproteins Gn and Gc, as well as putative nonstructural proteins NSs and NSm. Distinct virion morphologies suggested ancient evolutionary divergence, with bunyavirus-typical morphology for FERV (spheres of 60–120 nm) as opposed to an unusual bimorphology for JONV (tubular virions of 60 × 600 nm and spheres of 80 nm). Both viruses were genetically equidistant from all other bunyaviruses, showing <15% amino acid identity in the RdRp palm domain. Both had different and unique conserved genome termini, as in separate bunyavirus genera. JONV and FERV define two novel sister taxons to the superclade of orthobunyaviruses, tospoviruses, and hantaviruses. Phylogenetic ancestral state reconstruction with probabilistic hypothesis testing suggested ancestral associations with arthropods at deep nodes throughout the bunyavirus tree. Our findings suggest an arthropod origin of bunyaviruses. Significance Knowledge of the origin and evolution of viruses provides important insight into virus emergence involving the acquisition of genes necessary for the infection of new host species or the development of pathogenicity. The family Bunyaviridae contains important arthropod-borne pathogens of humans, animals, and plants. In this study, we provide a comprehensive characterization of two novel lineages of insect-specific bunyaviruses that are in basal phylogenetic relationship to the rodent-borne hantaviruses, the only genus within the Bunyaviridae that is not transmitted by arthropod vectors. These data, together with ancestral state reconstruction of bunyavirus hosts for major virus lineage bifurcations, suggest that the vertebrate-infecting viruses evolved from arthropod-specific progenitors.

As both a computational and an experimental endeavor, ancestral sequence reconstruction remains a timely and important technique. Modern approaches to conduct ancestral sequence reconstruction for proteins are built upon a conceptual framework from journal founder Emile Zuckerkandl. On top of this, work on maximum likelihood phylogenetics published in Journal of Molecular Evolution in 1996 was one of the first approaches for generating maximum likelihood ancestral sequences of proteins. From its computational history, future model development needs as well as potential applications in areas as diverse as computational systems biology, molecular community ecology, infectious disease therapeutics and other biomedical applications, and biotechnology are discussed. From its past in this journal, there is a bright future for ancestral sequence reconstruction in the field of evolutionary biology.