Automatic cell-type harmonization and integration across Human Cell Atlas datasets.

Harmonizing cell types across the single-cell community and assembling them into a common framework is central to building a standardized Human Cell Atlas. Here, we present CellHint, a predictive clustering tree-based tool to resolve cell-type differences in annotation resolution and technical biases across datasets. CellHint accurately quantifies cell-cell transcriptomic similarities and places cell types into a relationship graph that hierarchically defines shared and unique cell subtypes. Application to multiple immune datasets recapitulates expert-curated annotations. CellHint also reveals underexplored relationships between healthy and diseased lung cell states in eight diseases. Furthermore, we present a workflow for fast cross-dataset integration guided by harmonized cell types and cell hierarchy, which uncovers underappreciated cell types in adult human hippocampus. Finally, we apply CellHint to 12 tissues from 38 datasets, providing a deeply curated cross-tissue database with ∼3.7 million cells and various machine learning models for automatic cell annotation across human tissues.

Humans with inherited T cell CD28 deficiency are susceptible to skin papillomaviruses but are otherwise healthy.

We study a patient with the human papilloma virus (HPV)-2-driven "tree-man" phenotype and two relatives with unusually severe HPV4-driven warts. The giant horns form an HPV-2-driven multifocal benign epithelial tumor overexpressing viral oncogenes in the epidermis basal layer. The patients are unexpectedly homozygous for a private CD28 variant. They have no detectable CD28 on their T cells, with the exception of a small contingent of revertant memory CD4+ T cells. T cell development is barely affected, and T cells respond to CD3 and CD2, but not CD28, costimulation. Although the patients do not display HPV-2- and HPV-4-reactive CD4+ T cells in vitro, they make antibodies specific for both viruses in vivo. CD28-deficient mice are susceptible to cutaneous infections with the mouse papillomavirus MmuPV1. The control of HPV-2 and HPV-4 in keratinocytes is dependent on the T cell CD28 co-activation pathway. Surprisingly, human CD28-dependent T cell responses are largely redundant for protective immunity.

Tropical trees inherit low-frequency somatic mutations.

A new study by Schmitt et al. revealed that somatic mutations in tropical trees are passed on to their offspring. Furthermore, the study noted that the majority of inherited mutations were present at low allelic frequencies within the tree.

The shared ancestry between the C9orf72 hexanucleotide repeat expansion and intermediate-length alleles using haplotype sharing trees and HAPTK.

The C9orf72 hexanucleotide repeat expansion (HRE) is a common genetic cause of amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD). The inheritance is autosomal dominant, but a high proportion of subjects with the mutation are simplex cases. One possible explanation is de novo expansions of unstable intermediate-length alleles (IAs). Using haplotype sharing trees (HSTs) with the haplotype analysis tool kit (HAPTK), we derived majority-based ancestral haplotypes of HRE samples and discovered that IAs containing ≥18-20 repeats share large haplotypes in common with the HRE. Using HSTs of HRE and IA samples, we demonstrate that the longer IA haplotypes are largely indistinguishable from HRE haplotypes and that several ≥18-20 IA haplotypes share over 5 Mb (>600 markers) haplotypes in common with the HRE haplotypes. These analysis tools allow physical understanding of the haplotype blocks shared with the majority-based ancestral haplotype. Our results demonstrate that the haplotypes with longer IAs belong to the same pool of haplotypes as the HRE and suggest that longer IAs represent potential premutation alleles.

Ancient trees are essential elements for high-mountain forest conservation: Linking the longevity of trees to their ecological function.

Mature forests and their extremely old trees are rare and threatened ancient vestiges in remote European high-mountain regions. Here, we analyze the role that extremely long-living trees have in mature forests biodiversity in relation to their singular traits underlying longevity. Tree size and age determine relative growth rates, bud abortion, and the water status of long-living trees. The oldest trees suffer indefectible age-related constraints but possess singular evolutionary traits defined by fitness adaptation, modular autonomy, and a resilient metabolism that allow them to have irreplaceable roles in the ecosystem as biodiversity anchors of vulnerable lichen species like Letharia vulpina. We suggest that the role of ancient trees as unique biodiversity reservoirs is linked to their singular physiological traits associated with longevity. The set of evolutionarily plastic tools that can only be provided by centuries or millennia of longevity helps the oldest trees of mature forests drive singular ecological relationships that are irreplaceable and necessary for ecosystem dynamics.

A species' response to spatial climatic variation does not predict its response to climate change.

The dominant paradigm for assessing ecological responses to climate change assumes that future states of individuals and populations can be predicted by current, species-wide performance variation across spatial climatic gradients. However, if the fates of ecological systems are better predicted by past responses to in situ climatic variation through time, this current analytical paradigm may be severely misleading. Empirically testing whether spatial or temporal climate responses better predict how species respond to climate change has been elusive, largely due to restrictive data requirements. Here, we leverage a newly collected network of ponderosa pine tree-ring time series to test whether statistically inferred responses to spatial versus temporal climatic variation better predict how trees have responded to recent climate change. When compared to observed tree growth responses to climate change since 1980, predictions derived from spatial climatic variation were wrong in both magnitude and direction. This was not the case for predictions derived from climatic variation through time, which were able to replicate observed responses well. Future climate scenarios through the end of the 21st century exacerbated these disparities. These results suggest that the currently dominant paradigm of forecasting the ecological impacts of climate change based on spatial climatic variation may be severely misleading over decadal to centennial timescales.

Low-frequency somatic mutations are heritable in tropical trees Dicorynia guianensis and Sextonia rubra.

Somatic mutations potentially play a role in plant evolution, but common expectations pertaining to plant somatic mutations remain insufficiently tested. Unlike in most animals, the plant germline is assumed to be set aside late in development, leading to the expectation that plants accumulate somatic mutations along growth. Therefore, several predictions were made on the fate of somatic mutations: mutations have generally low frequency in plant tissues; mutations at high frequency have a higher chance of intergenerational transmission; branching topology of the tree dictates mutation distribution; and exposure to UV (ultraviolet) radiation increases mutagenesis. To provide insights into mutation accumulation and transmission in plants, we produced two high-quality reference genomes and a unique dataset of 60 high-coverage whole-genome sequences of two tropical tree species, Dicorynia guianensis (Fabaceae) and Sextonia rubra (Lauraceae). We identified 15,066 de novo somatic mutations in D. guianensis and 3,208 in S. rubra, surprisingly almost all found at low frequency. We demonstrate that 1) low-frequency mutations can be transmitted to the next generation; 2) mutation phylogenies deviate from the branching topology of the tree; and 3) mutation rates and mutation spectra are not demonstrably affected by differences in UV exposure. Altogether, our results suggest far more complex links between plant growth, aging, UV exposure, and mutation rates than commonly thought.

Mechanistic links between physiology and spectral reflectance enable previsual detection of oak wilt and drought stress.

Tree mortality due to global change-including range expansion of invasive pests and pathogens-is a paramount threat to forest ecosystems. Oak forests are among the most prevalent and valuable ecosystems both ecologically and economically in the United States. There is increasing interest in monitoring oak decline and death due to both drought and the oak wilt pathogen (Bretziella fagacearum). We combined anatomical and ecophysiological measurements with spectroscopy at leaf, canopy, and airborne levels to enable differentiation of oak wilt and drought, and detection prior to visible symptom appearance. We performed an outdoor potted experiment with Quercus rubra saplings subjected to drought stress and/or artificially inoculated with the pathogen. Models developed from spectral reflectance accurately predicted ecophysiological indicators of oak wilt and drought decline in both potted and field experiments with naturally grown saplings. Both oak wilt and drought resulted in blocked water transport through xylem conduits. However, oak wilt impaired conduits in localized regions of the xylem due to formation of tyloses instead of emboli. The localized tylose formation resulted in more variable canopy photosynthesis and water content in diseased trees than drought-stressed ones. Reflectance signatures of plant photosynthesis, water content, and cellular damage detected oak wilt and drought 12 d before visual symptoms appeared. Our results show that leaf spectral reflectance models predict ecophysiological processes relevant to detection and differentiation of disease and drought. Coupling spectral models that detect physiological change with spatial information enhances capacity to differentiate plant stress types such as oak wilt and drought.

Deficiency of primate-specific SSX1 induced asthenoteratozoospermia in infertile men and cynomolgus monkey and tree shrew models.

Primate-specific genes (PSGs) tend to be expressed in the brain and testis. This phenomenon is consistent with brain evolution in primates but is seemingly contradictory to the similarity of spermatogenesis among mammals. Here, using whole-exome sequencing, we identified deleterious variants of X-linked SSX1 in six unrelated men with asthenoteratozoospermia. SSX1 is a PSG expressed predominantly in the testis, and the SSX family evolutionarily expanded independently in rodents and primates. As the mouse model could not be used for studying SSX1, we used a non-human primate model and tree shrews, which are phylogenetically similar to primates, to knock down (KD) Ssx1 expression in the testes. Consistent with the phenotype observed in humans, both Ssx1-KD models exhibited a reduced sperm motility and abnormal sperm morphology. Further, RNA sequencing indicated that Ssx1 deficiency influenced multiple biological processes during spermatogenesis. Collectively, our experimental observations in humans and cynomolgus monkey and tree shrew models highlight the crucial role of SSX1 in spermatogenesis. Notably, three of the five couples who underwent intra-cytoplasmic sperm injection treatment achieved a successful pregnancy. This study provides important guidance for genetic counseling and clinical diagnosis and, significantly, describes the approaches for elucidating the functions of testis-enriched PSGs in spermatogenesis.

Reconstruction of gene regulatory networks for Caenorhabditis elegans using tree-shaped gene expression data.

Constructing gene regulatory networks is a widely adopted approach for investigating gene regulation, offering diverse applications in biology and medicine. A great deal of research focuses on using time series data or single-cell RNA-sequencing data to infer gene regulatory networks. However, such gene expression data lack either cellular or temporal information. Fortunately, the advent of time-lapse confocal laser microscopy enables biologists to obtain tree-shaped gene expression data of Caenorhabditis elegans, achieving both cellular and temporal resolution. Although such tree-shaped data provide abundant knowledge, they pose challenges like non-pairwise time series, laying the inaccuracy of downstream analysis. To address this issue, a comprehensive framework for data integration and a novel Bayesian approach based on Boolean network with time delay are proposed. The pre-screening process and Markov Chain Monte Carlo algorithm are applied to obtain the parameter estimates. Simulation studies show that our method outperforms existing Boolean network inference algorithms. Leveraging the proposed approach, gene regulatory networks for five subtrees are reconstructed based on the real tree-shaped datatsets of Caenorhabditis elegans, where some gene regulatory relationships confirmed in previous genetic studies are recovered. Also, heterogeneity of regulatory relationships in different cell lineage subtrees is detected. Furthermore, the exploration of potential gene regulatory relationships that bear importance in human diseases is undertaken. All source code is available at the GitHub repository https://github.com/edawu11/BBTD.git.

Phylogenetic inference of inter-population transmission rates for infectious diseases.

Estimating transmission rates is a challenging yet essential aspect of comprehending and controlling the spread of infectious diseases. Various methods exist for estimating transmission rates, each with distinct assumptions, data needs, and constraints. This study introduces a novel phylogenetic approach called transRate, which integrates genetic information with traditional epidemiological approaches to estimate inter-population transmission rates. The phylogenetic method is statistically consistent as the sample size (i.e. the number of pathogen genomes) approaches infinity under the multi-population susceptible-infected-recovered model. Simulation analyses indicate that transRate can accurately estimate the transmission rate with a sample size of 200 ~ 400 pathogen genomes. Using transRate, we analyzed 40,028 high-quality sequences of SARS-CoV-2 in human hosts during the early pandemic. Our analysis uncovered significant transmission between populations even before widespread travel restrictions were implemented. The development of transRate provides valuable insights for scientists and public health officials to enhance their understanding of the pandemic's progression and aiding in preparedness for future viral outbreaks. As public databases for genomic sequences continue to expand, transRate is increasingly vital for tracking and mitigating the spread of infectious diseases.

Integrating Reinforcement Learning and Monte Carlo Tree Search for enhanced neoantigen vaccine design.

Recent advances in cancer immunotherapy have highlighted the potential of neoantigen-based vaccines. However, the design of such vaccines is hindered by the possibility of weak binding affinity between the peptides and the patient's specific human leukocyte antigen (HLA) alleles, which may not elicit a robust adaptive immune response. Triggering cross-immunity by utilizing peptide mutations that have enhanced binding affinity to target HLA molecules, while preserving their homology with the original one, can be a promising avenue for neoantigen vaccine design. In this study, we introduced UltraMutate, a novel algorithm that combines Reinforcement Learning and Monte Carlo Tree Search, which identifies peptide mutations that not only exhibit enhanced binding affinities to target HLA molecules but also retains a high degree of homology with the original neoantigen. UltraMutate outperformed existing state-of-the-art methods in identifying affinity-enhancing mutations in an independent test set consisting of 3660 peptide-HLA pairs. UltraMutate further showed its applicability in the design of peptide vaccines for Human Papillomavirus and Human Cytomegalovirus, demonstrating its potential as a promising tool in the advancement of personalized immunotherapy.

Biolinguistic graph fusion model for circRNA-miRNA association prediction.

Emerging clinical evidence suggests that sophisticated associations with circular ribonucleic acids (RNAs) (circRNAs) and microRNAs (miRNAs) are a critical regulatory factor of various pathological processes and play a critical role in most intricate human diseases. Nonetheless, the above correlations via wet experiments are error-prone and labor-intensive, and the underlying novel circRNA-miRNA association (CMA) has been validated by numerous existing computational methods that rely only on single correlation data. Considering the inadequacy of existing machine learning models, we propose a new model named BGF-CMAP, which combines the gradient boosting decision tree with natural language processing and graph embedding methods to infer associations between circRNAs and miRNAs. Specifically, BGF-CMAP extracts sequence attribute features and interaction behavior features by Word2vec and two homogeneous graph embedding algorithms, large-scale information network embedding and graph factorization, respectively. Multitudinous comprehensive experimental analysis revealed that BGF-CMAP successfully predicted the complex relationship between circRNAs and miRNAs with an accuracy of 82.90% and an area under receiver operating characteristic of 0.9075. Furthermore, 23 of the top 30 miRNA-associated circRNAs of the studies on data were confirmed in relevant experiences, showing that the BGF-CMAP model is superior to others. BGF-CMAP can serve as a helpful model to provide a scientific theoretical basis for the study of CMA prediction.

New plastids, old proteins: repeated endosymbiotic acquisitions in kareniacean dinoflagellates.

Dinoflagellates are a diverse group of ecologically significant micro-eukaryotes that can serve as a model system for plastid symbiogenesis due to their susceptibility to plastid loss and replacement via serial endosymbiosis. Kareniaceae harbor fucoxanthin-pigmented plastids instead of the ancestral peridinin-pigmented ones and support them with a diverse range of nucleus-encoded plastid-targeted proteins originating from the haptophyte endosymbiont, dinoflagellate host, and/or lateral gene transfers (LGT). Here, we present predicted plastid proteomes from seven distantly related kareniaceans in three genera (Karenia, Karlodinium, and Takayama) and analyze their evolutionary patterns using automated tree building and sorting. We project a relatively limited ( ~ 10%) haptophyte signal pointing towards a shared origin in the family Chrysochromulinaceae. Our data establish significant variations in the functional distributions of these signals, emphasizing the importance of micro-evolutionary processes in shaping the chimeric proteomes. Analysis of plastid genome sequences recontextualizes these results by a striking finding the extant kareniacean plastids are in fact not all of the same origin, as two of the studied species (Karlodinium armiger, Takayama helix) possess plastids from different haptophyte orders than the rest.

The contours of evolution: In defence of Darwin's tree of life paradigm.

Both the concept of a Darwinian tree of life (TOL) and the possibility of its accurate reconstruction have been much criticized. Criticisms mostly revolve around the extensive occurrence of lateral gene transfer (LGT), instances of uptake of complete organisms to become organelles (with the associated subsequent gene transfer to the nucleus), as well as the implications of more subtle aspects of the biological species concept. Here we argue that none of these criticisms are sufficient to abandon the valuable TOL concept and the biological realities it captures. Especially important is the need to conceptually distinguish between organismal trees and gene trees, which necessitates incorporating insights of widely occurring LGT into modern evolutionary theory. We demonstrate that all criticisms, while based on important new findings, do not invalidate the TOL. After considering the implications of these new insights, we find that the contours of evolution are best represented by a TOL.

Climate change, tree demography, and thermophilization in western US forests.

Climate change is driving widespread changes in ecological communities. Warming temperatures often shift community composition toward more heat-tolerant taxa. The factors influencing the rate of this "thermophilization" process remain unclear. Using 10-y census data from an extensive forest plot network, we show that mature tree communities of the western United States have undergone thermophilization. The mean magnitude of climate warming over the 10-y study interval was 0.32 °C, whereas the mean magnitude of thermophilization was 0.039 °C. Differential tree mortality was the strongest demographic driver of thermophilization, rather than growth or recruitment. Thermophilization rates are associated with recent changes in temperature and hydrologic variables, as well as topography and disturbance, with insect damage showing the strongest standardized effect on thermophilization rates. On average, thermophilization occurred more rapidly on cool, north-facing hillslopes. Our results demonstrate that warming temperatures are outpacing the composition of western US forest tree communities, and that climate change may erode biodiversity patterns structured by topographic variation.

Tree architecture: A strigolactone-deficient mutant reveals a connection between branching order and auxin gradient along the tree stem.

Due to their long lifespan, trees and bushes develop higher order of branches in a perennial manner. In contrast to a tall tree, with a clearly defined main stem and branching order, a bush is shorter and has a less apparent main stem and branching pattern. To address the developmental basis of these two forms, we studied several naturally occurring architectural variants in silver birch (Betula pendula). Using a candidate gene approach, we identified a bushy kanttarelli variant with a loss-of-function mutation in the BpMAX1 gene required for strigolactone (SL) biosynthesis. While kanttarelli is shorter than the wild type (WT), it has the same number of primary branches, whereas the number of secondary branches is increased, contributing to its bush-like phenotype. To confirm that the identified mutation was responsible for the phenotype, we phenocopied kanttarelli in transgenic BpMAX1::RNAi birch lines. SL profiling confirmed that both kanttarelli and the transgenic lines produced very limited amounts of SL. Interestingly, the auxin (IAA) distribution along the main stem differed between WT and BpMAX1::RNAi. In the WT, the auxin concentration formed a gradient, being higher in the uppermost internodes and decreasing toward the basal part of the stem, whereas in the transgenic line, this gradient was not observed. Through modeling, we showed that the different IAA distribution patterns may result from the difference in the number of higher-order branches and plant height. Future studies will determine whether the IAA gradient itself regulates aspects of plant architecture.

Warming-induced tree growth may help offset increasing disturbance across the Canadian boreal forest.

Large projected increases in forest disturbance pose a major threat to future wood fiber supply and carbon sequestration in the cold-limited, Canadian boreal forest ecosystem. Given the large sensitivity of tree growth to temperature, warming-induced increases in forest productivity have the potential to reduce these threats, but research efforts to date have yielded contradictory results attributed to limited data availability, methodological biases, and regional variability in forest dynamics. Here, we apply a machine learning algorithm to an unprecedented network of over 1 million tree growth records (1958 to 2018) from 20,089 permanent sample plots distributed across both Canada and the United States, spanning a 16.5 °C climatic gradient. Fitted models were then used to project the near-term (2050 s time period) growth of the six most abundant tree species in the Canadian boreal forest. Our results reveal a large, positive effect of increasing thermal energy on tree growth for most of the target species, leading to 20.5 to 22.7% projected gains in growth with climate change under RCP 4.5 and 8.5. The magnitude of these gains, which peak in the colder and wetter regions of the boreal forest, suggests that warming-induced growth increases should no longer be considered marginal but may in fact significantly offset some of the negative impacts of projected increases in drought and wildfire on wood supply and carbon sequestration and have major implications on ecological forecasts and the global economy.

Mutilation of the tree of life via mass extinction of animal genera.

Mass extinctions during the past 500 million y rapidly removed branches from the phylogenetic tree of life and required millions of years for evolution to generate functional replacements for the extinct (EX) organisms. Here we show, by examining 5,400 vertebrate genera (excluding fishes) comprising 34,600 species, that 73 genera became EX since 1500 AD. Beyond any doubt, the human-driven sixth mass extinction is more severe than previously assessed and is rapidly accelerating. The current generic extinction rates are 35 times higher than expected background rates prevailing in the last million years under the absence of human impacts. The genera lost in the last five centuries would have taken some 18,000 y to vanish in the absence of human beings. Current generic extinction rates will likely greatly accelerate in the next few decades due to drivers accompanying the growth and consumption of the human enterprise such as habitat destruction, illegal trade, and climate disruption. If all now-endangered genera were to vanish by 2,100, extinction rates would be 354 (average) or 511 (for mammals) times higher than background rates, meaning that genera lost in three centuries would have taken 106,000 and 153,000 y to become EX in the absence of humans. Such mutilation of the tree of life and the resulting loss of ecosystem services provided by biodiversity to humanity is a serious threat to the stability of civilization. Immediate political, economic, and social efforts of an unprecedented scale are essential if we are to prevent these extinctions and their societal impacts.

The ground offers acoustic efficiency gains for crickets and other calling animals.

Male crickets attract females by producing calls with their forewings. Louder calls travel further and are more effective at attracting mates. However, crickets are much smaller than the wavelength of their call, and this limits their power output. A small group called tree crickets make acoustic tools called baffles which reduce acoustic short-circuiting, a source of dipole inefficiency. Here, we ask why baffling is uncommon among crickets. We hypothesize that baffling may be rare because like other tools they offer insufficient advantage for most species. To test this, we modelled the calling efficiencies of crickets within the full space of possible natural wing sizes and call frequencies, in multiple acoustic environments. We then generated efficiency landscapes, within which we plotted 112 cricket species across 7 phylogenetic clades. We found that all sampled crickets, in all conditions, could gain efficiency from tool use. Surprisingly, we also found that calling from the ground significantly increased efficiency, with or without a baffle, by as much as an order of magnitude. We found that the ground provides some reduction of acoustic short-circuiting but also halves the air volume within which sound is radiated. It simultaneously reflects sound upwards, allowing recapture of a significant amount of acoustic energy through constructive interference. Thus, using the ground as a reflective baffle is an effective strategy for increasing calling efficiency. Indeed, theory suggests that this increase in efficiency is accessible not just to crickets but to all acoustically communicating animals whether they are dipole or monopole sound sources.