Genetic tracing of market wildlife and viruses at the epicenter of the COVID-19 pandemic.

Zoonotic spillovers of viruses have occurred through the animal trade worldwide. The start of the COVID-19 pandemic was traced epidemiologically to the Huanan Seafood Wholesale Market. Here, we analyze environmental qPCR and sequencing data collected in the Huanan market in early 2020. We demonstrate that market-linked severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) genetic diversity is consistent with market emergence and find increased SARS-CoV-2 positivity near and within a wildlife stall. We identify wildlife DNA in all SARS-CoV-2-positive samples from this stall, including species such as civets, bamboo rats, and raccoon dogs, previously identified as possible intermediate hosts. We also detect animal viruses that infect raccoon dogs, civets, and bamboo rats. Combining metagenomic and phylogenetic approaches, we recover genotypes of market animals and compare them with those from farms and other markets. This analysis provides the genetic basis for a shortlist of potential intermediate hosts of SARS-CoV-2 to prioritize for serological and viral sampling.

Underdetected dispersal and extensive local transmission drove the 2022 mpox epidemic.

The World Health Organization declared mpox a public health emergency of international concern in July 2022. To investigate global mpox transmission and population-level changes associated with controlling spread, we built phylogeographic and phylodynamic models to analyze MPXV genomes from five global regions together with air traffic and epidemiological data. Our models reveal community transmission prior to detection, changes in case reporting throughout the epidemic, and a large degree of transmission heterogeneity. We find that viral introductions played a limited role in prolonging spread after initial dissemination, suggesting that travel bans would have had only a minor impact. We find that mpox transmission in North America began declining before more than 10% of high-risk individuals in the USA had vaccine-induced immunity. Our findings highlight the importance of broader routine specimen screening surveillance for emerging infectious diseases and of joint integration of genomic and epidemiological information for early outbreak control.

Dispersal patterns and influence of air travel during the global expansion of SARS-CoV-2 variants of concern.

The Alpha, Beta, and Gamma SARS-CoV-2 variants of concern (VOCs) co-circulated globally during 2020 and 2021, fueling waves of infections. They were displaced by Delta during a third wave worldwide in 2021, which, in turn, was displaced by Omicron in late 2021. In this study, we use phylogenetic and phylogeographic methods to reconstruct the dispersal patterns of VOCs worldwide. We find that source-sink dynamics varied substantially by VOC and identify countries that acted as global and regional hubs of dissemination. We demonstrate the declining role of presumed origin countries of VOCs in their global dispersal, estimating that India contributed <15% of Delta exports and South Africa <1%-2% of Omicron dispersal. We estimate that >80 countries had received introductions of Omicron within 100 days of its emergence, associated with accelerated passenger air travel and higher transmissibility. Our study highlights the rapid dispersal of highly transmissible variants, with implications for genomic surveillance along the hierarchical airline network.

Genomic surveillance reveals dynamic shifts in the connectivity of COVID-19 epidemics.

The maturation of genomic surveillance in the past decade has enabled tracking of the emergence and spread of epidemics at an unprecedented level. During the COVID-19 pandemic, for example, genomic data revealed that local epidemics varied considerably in the frequency of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) lineage importation and persistence, likely due to a combination of COVID-19 restrictions and changing connectivity. Here, we show that local COVID-19 epidemics are driven by regional transmission, including across international boundaries, but can become increasingly connected to distant locations following the relaxation of public health interventions. By integrating genomic, mobility, and epidemiological data, we find abundant transmission occurring between both adjacent and distant locations, supported by dynamic mobility patterns. We find that changing connectivity significantly influences local COVID-19 incidence. Our findings demonstrate a complex meaning of "local" when investigating connected epidemics and emphasize the importance of collaborative interventions for pandemic prevention and mitigation.

Stepwise emergence of the neuronal gene expression program in early animal evolution.

The assembly of the neuronal and other major cell type programs occurred early in animal evolution. We can reconstruct this process by studying non-bilaterians like placozoans. These small disc-shaped animals not only have nine morphologically described cell types and no neurons but also show coordinated behaviors triggered by peptide-secreting cells. We investigated possible neuronal affinities of these peptidergic cells using phylogenetics, chromatin profiling, and comparative single-cell genomics in four placozoans. We found conserved cell type expression programs across placozoans, including populations of transdifferentiating and cycling cells, suggestive of active cell type homeostasis. We also uncovered fourteen peptidergic cell types expressing neuronal-associated components like the pre-synaptic scaffold that derive from progenitor cells with neurogenesis signatures. In contrast, earlier-branching animals like sponges and ctenophores lacked this conserved expression. Our findings indicate that key neuronal developmental and effector gene modules evolved before the advent of cnidarian/bilaterian neurons in the context of paracrine cell signaling.

Lineage tracing reveals the phylodynamics, plasticity, and paths of tumor evolution.

Tumor evolution is driven by the progressive acquisition of genetic and epigenetic alterations that enable uncontrolled growth and expansion to neighboring and distal tissues. The study of phylogenetic relationships between cancer cells provides key insights into these processes. Here, we introduced an evolving lineage-tracing system with a single-cell RNA-seq readout into a mouse model of Kras;Trp53(KP)-driven lung adenocarcinoma and tracked tumor evolution from single-transformed cells to metastatic tumors at unprecedented resolution. We found that the loss of the initial, stable alveolar-type2-like state was accompanied by a transient increase in plasticity. This was followed by the adoption of distinct transcriptional programs that enable rapid expansion and, ultimately, clonal sweep of stable subclones capable of metastasizing. Finally, tumors develop through stereotypical evolutionary trajectories, and perturbing additional tumor suppressors accelerates progression by creating novel trajectories. Our study elucidates the hierarchical nature of tumor evolution and, more broadly, enables in-depth studies of tumor progression.

Emergence of an early SARS-CoV-2 epidemic in the United States.

The emergence of the COVID-19 epidemic in the United States (U.S.) went largely undetected due to inadequate testing. New Orleans experienced one of the earliest and fastest accelerating outbreaks, coinciding with Mardi Gras. To gain insight into the emergence of SARS-CoV-2 in the U.S. and how large-scale events accelerate transmission, we sequenced SARS-CoV-2 genomes during the first wave of the COVID-19 epidemic in Louisiana. We show that SARS-CoV-2 in Louisiana had limited diversity compared to other U.S. states and that one introduction of SARS-CoV-2 led to almost all of the early transmission in Louisiana. By analyzing mobility and genomic data, we show that SARS-CoV-2 was already present in New Orleans before Mardi Gras, and the festival dramatically accelerated transmission. Our study provides an understanding of how superspreading during large-scale events played a key role during the early outbreak in the U.S. and can greatly accelerate epidemics.

Early introductions and transmission of SARS-CoV-2 variant B.1.1.7 in the United States.

The emergence and spread of SARS-CoV-2 lineage B.1.1.7, first detected in the United Kingdom, has become a global public health concern because of its increased transmissibility. Over 2,500 COVID-19 cases associated with this variant have been detected in the United States (US) since December 2020, but the extent of establishment is relatively unknown. Using travel, genomic, and diagnostic data, we highlight that the primary ports of entry for B.1.1.7 in the US were in New York, California, and Florida. Furthermore, we found evidence for many independent B.1.1.7 establishments starting in early December 2020, followed by interstate spread by the end of the month. Finally, we project that B.1.1.7 will be the dominant lineage in many states by mid- to late March. Thus, genomic surveillance for B.1.1.7 and other variants urgently needs to be enhanced to better inform the public health response.

Illuminating Genetic Mysteries of the Dead Sea Scrolls.

The discovery of the 2,000-year-old Dead Sea Scrolls had an incomparable impact on the historical understanding of Judaism and Christianity. "Piecing together" scroll fragments is like solving jigsaw puzzles with an unknown number of missing parts. We used the fact that most scrolls are made from animal skins to "fingerprint" pieces based on DNA sequences. Genetic sorting of the scrolls illuminates their textual relationship and historical significance. Disambiguating the contested relationship between Jeremiah fragments supplies evidence that some scrolls were brought to the Qumran caves from elsewhere; significantly, they demonstrate that divergent versions of Jeremiah circulated in parallel throughout Israel (ancient Judea). Similarly, patterns discovered in non-biblical scrolls, particularly the Songs of the Sabbath Sacrifice, suggest that the Qumran scrolls represent the broader cultural milieu of the period. Finally, genetic analysis divorces debated fragments from the Qumran scrolls. Our study demonstrates that interdisciplinary approaches enrich the scholar's toolkit.

Coast-to-Coast Spread of SARS-CoV-2 during the Early Epidemic in the United States.

The novel coronavirus SARS-CoV-2 was first detected in the Pacific Northwest region of the United States in January 2020, with subsequent COVID-19 outbreaks detected in all 50 states by early March. To uncover the sources of SARS-CoV-2 introductions and patterns of spread within the United States, we sequenced nine viral genomes from early reported COVID-19 patients in Connecticut. Our phylogenetic analysis places the majority of these genomes with viruses sequenced from Washington state. By coupling our genomic data with domestic and international travel patterns, we show that early SARS-CoV-2 transmission in Connecticut was likely driven by domestic introductions. Moreover, the risk of domestic importation to Connecticut exceeded that of international importation by mid-March regardless of our estimated effects of federal travel restrictions. This study provides evidence of widespread sustained transmission of SARS-CoV-2 within the United States and highlights the critical need for local surveillance.

Genomic Epidemiology of SARS-CoV-2 in Guangdong Province, China.

Coronavirus disease 2019 (COVID-19) is caused by SARS-CoV-2 infection and was first reported in central China in December 2019. Extensive molecular surveillance in Guangdong, China's most populous province, during early 2020 resulted in 1,388 reported RNA-positive cases from 1.6 million tests. In order to understand the molecular epidemiology and genetic diversity of SARS-CoV-2 in China, we generated 53 genomes from infected individuals in Guangdong using a combination of metagenomic sequencing and tiling amplicon approaches. Combined epidemiological and phylogenetic analyses indicate multiple independent introductions to Guangdong, although phylogenetic clustering is uncertain because of low virus genetic variation early in the pandemic. Our results illustrate how the timing, size, and duration of putative local transmission chains were constrained by national travel restrictions and by the province's large-scale intensive surveillance and intervention measures. Despite these successes, COVID-19 surveillance in Guangdong is still required, because the number of cases imported from other countries has increased.

Travel Surveillance and Genomics Uncover a Hidden Zika Outbreak during the Waning Epidemic.

The Zika epidemic in the Americas has challenged surveillance and control. As the epidemic appears to be waning, it is unclear whether transmission is still ongoing, which is exacerbated by discrepancies in reporting. To uncover locations with lingering outbreaks, we investigated travel-associated Zika cases to identify transmission not captured by reporting. We uncovered an unreported outbreak in Cuba during 2017, a year after peak transmission in neighboring islands. By sequencing Zika virus, we show that the establishment of the virus was delayed by a year and that the ensuing outbreak was sparked by long-lived lineages of Zika virus from other Caribbean islands. Our data suggest that, although mosquito control in Cuba may initially have been effective at mitigating Zika virus transmission, such measures need to be maintained to be effective. Our study highlights how Zika virus may still be "silently" spreading and provides a framework for understanding outbreak dynamics. VIDEO ABSTRACT.

Tempo and Mode of Genome Evolution in the Budding Yeast Subphylum.

Budding yeasts (subphylum Saccharomycotina) are found in every biome and are as genetically diverse as plants or animals. To understand budding yeast evolution, we analyzed the genomes of 332 yeast species, including 220 newly sequenced ones, which represent nearly one-third of all known budding yeast diversity. Here, we establish a robust genus-level phylogeny comprising 12 major clades, infer the timescale of diversification from the Devonian period to the present, quantify horizontal gene transfer (HGT), and reconstruct the evolution of 45 metabolic traits and the metabolic toolkit of the budding yeast common ancestor (BYCA). We infer that BYCA was metabolically complex and chronicle the tempo and mode of genomic and phenotypic evolution across the subphylum, which is characterized by very low HGT levels and widespread losses of traits and the genes that control them. More generally, our results argue that reductive evolution is a major mode of evolutionary diversification.

Widespread adaptive evolution in angiosperm photosystems provides insight into the evolution of photosystem II repair.

Oxygenic photosynthesis generates the initial energy source that fuels nearly all life on Earth. At the heart of the process are the photosystems, which are pigment binding multi-protein complexes that catalyse the first step of photochemical conversion of light energy into chemical energy. Here, we investigate the molecular evolution of the plastid-encoded photosystem subunits at single-residue resolution across 773 angiosperm species. We show that despite an extremely high level of conservation, 7% of residues in the photosystems, spanning all photosystem subunits, exhibit hallmarks of adaptive evolution. Through in silico modelling of these adaptive substitutions, we uncover the impact of these changes on the predicted properties of the photosystems, focussing on their effects on co-factor binding and inter-subunit interface formation. By analyzing these cohorts of changes, we reveal that evolution has repeatedly altered the interaction between photosystem II and its D1 subunit in a manner that is predicted to reduce the energetic barrier for D1 turnover and photosystem repair. Together, these results provide insight into the trajectory of photosystem adaptation during angiosperm evolution.

B cell phylogenetics in the single cell era.

The widespread availability of single-cell RNA sequencing (scRNA-seq) has led to the development of new methods for understanding immune responses. Single-cell transcriptome data can now be paired with B cell receptor (BCR) sequences. However, RNA from BCRs cannot be analyzed like most other genes because BCRs are genetically diverse within individuals. In humans, BCRs are shaped through recombination followed by mutation and selection for antigen binding. As these processes co-occur with cell division, B cells can be studied using phylogenetic trees representing the mutations within a clone. B cell trees can link experimental timepoints, tissues, or cellular subtypes. Here, we review the current state and potential of how B cell phylogenetics can be combined with single-cell data to understand immune responses.

The receptor-like kinase ARK controls symbiotic balance across land plants.

The mutualistic arbuscular mycorrhizal (AM) symbiosis arose in land plants more than 450 million years ago and is still widely found in all major land plant lineages. Despite its broad taxonomic distribution, little is known about the molecular components underpinning symbiosis outside of flowering plants. The ARBUSCULAR RECEPTOR-LIKE KINASE (ARK) is required for sustaining AM symbiosis in distantly related angiosperms. Here, we demonstrate that ARK has an equivalent role in symbiosis maintenance in the bryophyte Marchantia paleacea and is part of a broad AM genetic program conserved among land plants. In addition, our comparative transcriptome analysis identified evolutionarily conserved expression patterns for several genes in the core symbiotic program required for presymbiotic signaling, intracellular colonization, and nutrient exchange. This study provides insights into the molecular pathways that consistently associate with AM symbiosis across land plants and identifies an ancestral role for ARK in governing symbiotic balance.

Unsupervised identification of significant lineages of SARS-CoV-2 through scalable machine learning methods.

Since its emergence in late 2019, SARS-CoV-2 has diversified into a large number of lineages and caused multiple waves of infection globally. Novel lineages have the potential to spread rapidly and internationally if they have higher intrinsic transmissibility and/or can evade host immune responses, as has been seen with the Alpha, Delta, and Omicron variants of concern. They can also cause increased mortality and morbidity if they have increased virulence, as was seen for Alpha and Delta. Phylogenetic methods provide the "gold standard" for representing the global diversity of SARS-CoV-2 and to identify newly emerging lineages. However, these methods are computationally expensive, struggle when datasets get too large, and require manual curation to designate new lineages. These challenges provide a motivation to develop complementary methods that can incorporate all of the genetic data available without down-sampling to extract meaningful information rapidly and with minimal curation. In this paper, we demonstrate the utility of using algorithmic approaches based on word-statistics to represent whole sequences, bringing speed, scalability, and interpretability to the construction of genetic topologies. While not serving as a substitute for current phylogenetic analyses, the proposed methods can be used as a complementary, and fully automatable, approach to identify and confirm new emerging variants.

Theoretical guarantees for phylogeny inference from single-cell lineage tracing.

Lineage-tracing technologies based on Clustered Regularly Interspaced Short Palindromic Repeats and CRISPR-associated protein 9 (CRISPR-Cas9) genome editing have emerged as a powerful tool for investigating development in single-cell contexts, but exact reconstruction of the underlying clonal relationships in experiment is complicated by features of the data. These complications are functions of the experimental parameters in these systems, such as the Cas9 cutting rate, the diversity of indel outcomes, and the rate of missing data. In this paper, we develop two theoretically grounded algorithms for the reconstruction of the underlying single-cell phylogenetic tree as well as asymptotic bounds for the number of recording sites necessary for exact recapitulation of the ground truth phylogeny at high probability. In doing so, we explore the relationship between the problem difficulty and the experimental parameters, with implications for experimental design. Lastly, we provide simulations showing the empirical performance of these algorithms and showing that the trends in the asymptotic bounds hold empirically. Overall, this work provides a theoretical analysis of phylogenetic reconstruction in single-cell CRISPR-Cas9 lineage-tracing technologies.

Origin of the OAS-RNase L innate immune pathway before the rise of jawed vertebrates via molecular tinkering.

Discriminating self from nonself is fundamental to immunity. Yet, it remains largely elusive how the mechanisms of self and nonself discrimination originated. Sensing double-stranded RNA as nonself, the 2',5'-oligoadenylate synthetase (OAS)-ribonuclease L (RNase L) pathway represents a crucial component of innate immunity. Here, we combine phylogenomic and functional analyses to show that the functional OAS-RNase L pathway likely originated through tinkering with preexisting proteins before the rise of jawed vertebrates during or before the Silurian period (444 to 419 Mya). Multiple concerted losses of OAS and RNase L occurred during the evolution of jawed vertebrates, further supporting the ancient coupling between OAS and RNase L. Moreover, both OAS and RNase L genes evolved under episodic positive selection across jawed vertebrates, suggesting a long-running evolutionary arms race between the OAS-RNase L pathway and microbes. Our findings illuminate how an innate immune pathway originated via molecular tinkering.

Mutation rates and adaptive variation among the clinically dominant clusters of Mycobacterium abscessus.

Mycobacterium abscessus (Mab) is a multidrug-resistant pathogen increasingly responsible for severe pulmonary infections. Analysis of whole-genome sequences (WGS) of Mab demonstrates dense genetic clustering of clinical isolates collected from disparate geographic locations. This has been interpreted as supporting patient-to-patient transmission, but epidemiological studies have contradicted this interpretation. Here, we present evidence for a slowing of the Mab molecular clock rate coincident with the emergence of phylogenetic clusters. We performed phylogenetic inference using publicly available WGS from 483 Mab patient isolates. We implement a subsampling approach in combination with coalescent analysis to estimate the molecular clock rate along the long internal branches of the tree, indicating a faster long-term molecular clock rate compared to branches within phylogenetic clusters. We used ancestry simulation to predict the effects of clock rate variation on phylogenetic clustering and found that the degree of clustering in the observed phylogeny is more easily explained by a clock rate slowdown than by transmission. We also find that phylogenetic clusters are enriched in mutations affecting DNA repair machinery and report that clustered isolates have lower spontaneous mutation rates in vitro. We propose that Mab adaptation to the host environment through variation in DNA repair genes affects the organism's mutation rate and that this manifests as phylogenetic clustering. These results challenge the model that phylogenetic clustering in Mab is explained by person-to-person transmission and inform our understanding of transmission inference in emerging, facultative pathogens.