A 2-million-year-old ecosystem in Greenland uncovered by environmental DNA.

Late Pliocene and Early Pleistocene epochs 3.6 to 0.8 million years ago1 had climates resembling those forecasted under future warming2. Palaeoclimatic records show strong polar amplification with mean annual temperatures of 11-19 °C above contemporary values3,4. The biological communities inhabiting the Arctic during this time remain poorly known because fossils are rare5. Here we report an ancient environmental DNA6 (eDNA) record describing the rich plant and animal assemblages of the Kap København Formation in North Greenland, dated to around two million years ago. The record shows an open boreal forest ecosystem with mixed vegetation of poplar, birch and thuja trees, as well as a variety of Arctic and boreal shrubs and herbs, many of which had not previously been detected at the site from macrofossil and pollen records. The DNA record confirms the presence of hare and mitochondrial DNA from animals including mastodons, reindeer, rodents and geese, all ancestral to their present-day and late Pleistocene relatives. The presence of marine species including horseshoe crab and green algae support a warmer climate than today. The reconstructed ecosystem has no modern analogue. The survival of such ancient eDNA probably relates to its binding to mineral surfaces. Our findings open new areas of genetic research, demonstrating that it is possible to track the ecology and evolution of biological communities from two million years ago using ancient eDNA.

Late Quaternary dynamics of Arctic biota from ancient environmental genomics.

During the last glacial-interglacial cycle, Arctic biotas experienced substantial climatic changes, yet the nature, extent and rate of their responses are not fully understood1-8. Here we report a large-scale environmental DNA metagenomic study of ancient plant and mammal communities, analysing 535 permafrost and lake sediment samples from across the Arctic spanning the past 50,000 years. Furthermore, we present 1,541 contemporary plant genome assemblies that were generated as reference sequences. Our study provides several insights into the long-term dynamics of the Arctic biota at the circumpolar and regional scales. Our key findings include: (1) a relatively homogeneous steppe-tundra flora dominated the Arctic during the Last Glacial Maximum, followed by regional divergence of vegetation during the Holocene epoch; (2) certain grazing animals consistently co-occurred in space and time; (3) humans appear to have been a minor factor in driving animal distributions; (4) higher effective precipitation, as well as an increase in the proportion of wetland plants, show negative effects on animal diversity; (5) the persistence of the steppe-tundra vegetation in northern Siberia enabled the late survival of several now-extinct megafauna species, including the woolly mammoth until 3.9 ± 0.2 thousand years ago (ka) and the woolly rhinoceros until 9.8 ± 0.2 ka; and (6) phylogenetic analysis of mammoth environmental DNA reveals a previously unsampled mitochondrial lineage. Our findings highlight the power of ancient environmental metagenomics analyses to advance understanding of population histories and long-term ecological dynamics.

Placing Ancient DNA Sequences into Reference Phylogenies.

Joint phylogenetic analysis of ancient DNA (aDNA) with modern phylogenies is hampered by low sequence coverage and post-mortem deamination, often resulting in overconservative or incorrect assignment. We provide a new efficient likelihood-based workflow, pathPhynder, that takes advantage of all the polymorphic sites in the target sequence. This effectively evaluates the number of ancestral and derived alleles present on each branch and reports the most likely placement of an ancient sample in the phylogeny and a haplogroup assignment, together with alternatives and supporting evidence. To illustrate the application of pathPhynder, we show improved Y chromosome assignments for published aDNA sequences, using a newly compiled Y variation data set (120,908 markers from 2,014 samples) that significantly enhances Y haplogroup assignment for low coverage samples. We apply the method to all published male aDNA samples from Africa, giving new insights into ancient migrations and the relationships between ancient and modern populations. The same software can be used to place samples with large amounts of missing data into other large non-recombining phylogenies such as the mitochondrial tree.

Wright-Fisher exact solver (WFES): scalable analysis of population genetic models without simulation or diffusion theory.

Motivation: The simplifying assumptions that are used widely in theoretical population genetics may not always be appropriate for empirical population genetics. General computational approaches that do not require the assumptions of classical theory are therefore quite desirable. One such general approach is provided by the theory of absorbing Markov chains, which can be used to obtain exact results by directly analyzing population genetic Markov models, such as the classic bi-allelic Wright-Fisher model. Although these approaches are sometimes used, they are usually forgone in favor of simulation methods, due to the perception that they are too computationally burdensome. Here we show that, surprisingly, direct analysis of virtually any Markov chain model in population genetics can be made quite efficient by exploiting transition matrix sparsity and by solving restricted systems of linear equations, allowing a wide variety of exact calculations (within machine precision) to be easily and rapidly made on modern workstation computers. Results: We introduce Wright-Fisher Exact Solver (WFES), a fast and scalable method for direct analysis of Markov chain models in population genetics. WFES can rapidly solve for both long-term and transient behaviours including fixation and extinction probabilities, expected times to fixation or extinction, sojourn times, expected allele age and variance, and others. Our implementation requires only seconds to minutes of runtime on modern workstations and scales to biological population sizes ranging from humans to model organisms. Availability and Implementation: The code is available at https://github.com/dekoning-lab/wfes. Contact: jason.dekoning@ucalgary.ca. Supplementary information: Supplementary data are available at Bioinformatics online.

Synthetic lethality and the minimal genome size problem.

Gene knockout studies suggest that ~300 genes in a bacterial genome and ~1,100 genes in a yeast genome cannot be deleted without loss of viability. These single-gene knockout experiments do not account for negative genetic interactions, when two or more genes can each be deleted without effect, but their joint deletion is lethal. Thus, large-scale single-gene deletion studies underestimate the size of a minimal gene set compatible with cell survival. In yeast Saccharomyces cerevisiae, the viability of all possible deletions of gene pairs (2-tuples), and of some deletions of gene triplets (3-tuples), has been experimentally tested. To estimate the size of a yeast minimal genome from that data, we first established that finding the size of a minimal gene set is equivalent to finding the minimum vertex cover in the lethality (hyper)graph, where the vertices are genes and (hyper)edges connect k-tuples of genes whose joint deletion is lethal. Using the Lovász-Johnson-Chvatal greedy approximation algorithm, we computed the minimum vertex cover of the synthetic-lethal 2-tuples graph to be 1,723 genes. We next simulated the genetic interactions in 3-tuples, extrapolating from the existing triplet sample, and again estimated minimum vertex covers. The size of a minimal gene set in yeast rapidly approaches the size of the entire genome even when considering only synthetic lethalities in k-tuples with small k. In contrast, several studies reported successful experimental reductions of yeast and bacterial genomes by simultaneous deletions of hundreds of genes, without eliciting synthetic lethality. We discuss possible reasons for this apparent contradiction.IMPORTANCEHow can we estimate the smallest number of genes sufficient for a unicellular organism to survive on a rich medium? One approach is to remove genes one at a time and count how many of such deletion strains are unable to grow. However, the single-gene knockout data are insufficient, because joint gene deletions may result in negative genetic interactions, also known as synthetic lethality. We used a technique from graph theory to estimate the size of minimal yeast genome from partial data on synthetic lethality. The number of potential synthetic lethal interactions grows very fast when multiple genes are deleted, revealing a paradoxical contrast with the experimental reductions of yeast genome by ~100 genes, and of bacterial genomes by several hundreds of genes.

Fisher's Geometric Model as a Tool to Study Speciation.

Interactions between alleles and across environments play an important role in the fitness of hybrids and are at the heart of the speciation process. Fitness landscapes capture these interactions and can be used to model hybrid fitness, helping us to interpret empirical observations and clarify verbal models. Here, we review recent progress in understanding hybridization outcomes through Fisher's geometric model, an intuitive and analytically tractable fitness landscape that captures many fitness patterns observed across taxa. We use case studies to show how the model parameters can be estimated from different types of data and discuss how these estimates can be used to make inferences about the divergence history and genetic architecture. We also highlight some areas where the model's predictions differ from alternative incompatibility-based models, such as the snowball effect and outlier patterns in genome scans.

Rotate: A command-line program to rotate circular DNA sequences to start at a given position or string.

Sequences derived from circular DNA molecules (i.e. most bacterial, viral and plastid genomes) are expected to be linearised and rotated to a common start position for most downstream analyses including alignment. Despite this being a common and straightforward task, available software is either limited to a small number of input sequences, lacks the option to specify a custom anchor string, or requires a commercial license. Here, we present rotate, a simple, open source command line program written in C with no external dependencies, which can rotate a set of input sequences to a custom anchor string (allowing for a specified number of mismatches), or offset the input sequences to the desired position. The combination of both functionalities allows the rotation of all input sequences to any desired starting position, enabling downstream analysis. rotate is extremely fast and scales linearly with the number of input sequences, taking only seconds to rotate over a thousand mitochondrial sequences.

A theoretical analysis of taxonomic binning accuracy.

Many metagenomic and environmental DNA studies require the taxonomic assignment of individual reads or sequences by aligning reads to a reference database, known as taxonomic binning. When a read aligns to more than one reference sequence, it is often classified based on sequence similarity. This step can assign reads to incorrect taxa, at a rate which depends both on the assignment algorithm and on underlying population genetic and database parameters. In particular, as we move towards using environmental DNA to study eukaryotic taxa subject to regular recombination, we must take into account issues concerning gene tree discordance. Though accuracy is often compared across algorithms using a fixed data set, the relative impact of these population genetic and database parameters on accuracy has not yet been quantified. Here, we develop both a theoretical and simulation framework in the simplified case of two reference species, and compute binning accuracy over a wide range of parameters, including sequence length, species-query divergence time, divergence times of the reference species, reference database completeness, sample age and effective population size. We consider two assignment methods and contextualize our results using parameters from a recent ancient environmental DNA study, comparing them to the commonly used discriminative k-mer-based method Clark (Current Biology, 31, 2021, 2728; BMC Genomics, 16, 2015, 1). Our results quantify the degradation in assignment accuracy as the samples diverge from their closest reference sequence, and with incompleteness of reference sequences. We also provide a framework in which others can compute expected accuracy for their particular method or parameter set. Code is available at https://github.com/bdesanctis/binning-accuracy.

Environmental genomics of Late Pleistocene black bears and giant short-faced bears.

Analysis of ancient environmental DNA (eDNA) has revolutionized our ability to describe biological communities in space and time,1-3 by allowing for parallel sequencing of DNA from all trophic levels.4-8 However, because environmental samples contain sparse and fragmented data from multiple individuals, and often contain closely related species,9 the field of ancient eDNA has so far been limited to organellar genomes in its contribution to population and phylogenetic studies.5,6,10,11 This is in contrast to data from fossils12,13 where full-genome studies are routine, despite these being rare and their destruction for sequencing undesirable.14-16 Here, we report the retrieval of three low-coverage (0.03×) environmental genomes from American black bear (Ursus americanus) and a 0.04× environmental genome of the extinct giant short-faced bear (Arctodus simus) from cave sediment samples from northern Mexico dated to 16-14 thousand calibrated years before present (cal kyr BP), which we contextualize with a new high-coverage (26×) and two lower-coverage giant short-faced bear genomes obtained from fossils recovered from Yukon Territory, Canada, which date to ∼22-50 cal kyr BP. We show that the Late Pleistocene black bear population in Mexico is ancestrally related to the present-day Eastern American black bear population, and that the extinct giant short-faced bears present in Mexico were deeply divergent from the earlier Beringian population. Our findings demonstrate the ability to separately analyze genomic-scale DNA sequences of closely related species co-preserved in environmental samples, which brings the use of ancient eDNA into the era of population genomics and phylogenetics.

The geometry and genetics of hybridization.

When divergent populations form hybrids, hybrid fitness can vary with genome composition, current environmental conditions, and the divergence history of the populations. We develop analytical predictions for hybrid fitness, which incorporate all three factors. The predictions are based on Fisher's geometric model, and apply to a wide range of population genetic parameter regimes and divergence conditions, including allopatry and parapatry, local adaptation, and drift. Results show that hybrid fitness can be decomposed into intrinsic effects of admixture and heterozygosity, and extrinsic effects of the (local) adaptedness of the parental lines. Effect sizes are determined by a handful of geometric distances, which have a simple biological interpretation. These distances also reflect the mode and amount of divergence, such that there is convergence toward a characteristic pattern of intrinsic isolation. We next connect our results to the quantitative genetics of line crosses in variable or patchy environments. This means that the geometrical distances can be estimated from cross data, and provides a simple interpretation of the "composite effects." Finally, we develop extensions to the model, involving selectively induced disequilibria, and variable phenotypic dominance. The geometry of fitness landscapes provides a unifying framework for understanding speciation, and wider patterns of hybrid fitness.

Allele Age Under Non-Classical Assumptions is Clarified by an Exact Computational Markov Chain Approach.

Determination of the age of an allele based on its population frequency is a well-studied problem in population genetics, for which a variety of approximations have been proposed. We present a new result that, surprisingly, allows the expectation and variance of allele age to be computed exactly (within machine precision) for any finite absorbing Markov chain model in a matter of seconds. This approach makes none of the classical assumptions (e.g., weak selection, reversibility, infinite sites), exploits modern sparse linear algebra techniques, integrates over all sample paths, and is rapidly computable for Wright-Fisher populations up to N e = 100,000. With this approach, we study the joint effect of recurrent mutation, dominance, and selection, and demonstrate new examples of "selective strolls" where the classical symmetry of allele age with respect to selection is violated by weakly selected alleles that are older than neutral alleles at the same frequency. We also show evidence for a strong age imbalance, where rare deleterious alleles are expected to be substantially older than advantageous alleles observed at the same frequency when population-scaled mutation rates are large. These results highlight the under-appreciated utility of computational methods for the direct analysis of Markov chain models in population genetics.

Cytotoxicity in the marine dinoflagellate Prorocentrum mexicanum from Brazil.

The microscopic algae in the oceans are crucial food for filter feeding bivalve shellfish (oysters, mussels, scallops, clams, etc.) as well as for the larvae of commercially important crustaceans. Some species of microalgae have the capacity to produce potent toxins, such as saxitoxins and ciguatoxins, which may intoxicate humans. Among the marine phytoplankton, the dinoflagellates are the main toxin producers. Studies on the marine phytoplankton from the São Sebastião Channel, southeastern coast of Brazil, showed a great diversity of dinoflagellates. Some species were collected and cultured at the Marine Biology Center of the São Paulo University (USP). The polar (PEs) (aqueous) and apolar (AEs) (methylene chloride) extracts of the cultivated dinoflagellate species were tested on different stages of the sea urchin development, on mouse erythrocytes and on microfilaments organization in a neuroblastoma cell line. Prorocentrum mexicanum PE and AE induced cells anomalies and cell division inhibition of sea urchin eggs at EC50 of 78.75 microg/mL (95% CI from 32.56 to 190.50) and 22.50 microg/mL (95% CI from 2.96 to 170.80) respectively (n=3). Both AE and PE of P. mexicanum induced hemolysis with EC50 of 65.07 microg/mL (95% CI from 27.40 to 154.60) and 84.29 microg/mL (95% CI from 53.26 to 133.40 microg/mL), respectively. P. mexicanum PE was tested in immunofluorescence for actin filaments organization in neuroblastoma cultured cell.