Metatranscriptomics captures dynamic shifts in mycorrhizal coordination in boreal forests.

Carbon storage and cycling in boreal forests-the largest terrestrial carbon store-is moderated by complex interactions between trees and soil microorganisms. However, existing methods limit our ability to predict how changes in environmental conditions will alter these associations and the essential ecosystem services they provide. To address this, we developed a metatranscriptomic approach to analyze the impact of nutrient enrichment on Norway spruce fine roots and the community structure, function, and tree-microbe coordination of over 350 root-associated fungal species. In response to altered nutrient status, host trees redefined their relationship with the fungal community by reducing sugar efflux carriers and enhancing defense processes. This resulted in a profound restructuring of the fungal community and a collapse in functional coordination between the tree and the dominant Basidiomycete species, and an increase in functional coordination with versatile Ascomycete species. As such, there was a functional shift in community dominance from Basidiomycetes species, with important roles in enzymatically cycling recalcitrant carbon, to Ascomycete species that have melanized cell walls that are highly resistant to degradation. These changes were accompanied by prominent shifts in transcriptional coordination between over 60 predicted fungal effectors, with more than 5,000 Norway spruce transcripts, providing mechanistic insight into the complex molecular dialogue coordinating host trees and their fungal partners. The host-microbe dynamics captured by this study functionally inform how these complex and sensitive biological relationships may mediate the carbon storage potential of boreal soils under changing nutrient conditions.

MindReader: Unsupervised Classification of Electroencephalographic Data.

Electroencephalogram (EEG) interpretation plays a critical role in the clinical assessment of neurological conditions, most notably epilepsy. However, EEG recordings are typically analyzed manually by highly specialized and heavily trained personnel. Moreover, the low rate of capturing abnormal events during the procedure makes interpretation time-consuming, resource-hungry, and overall an expensive process. Automatic detection offers the potential to improve the quality of patient care by shortening the time to diagnosis, managing big data and optimizing the allocation of human resources towards precision medicine. Here, we present MindReader, a novel unsupervised machine-learning method comprised of the interplay between an autoencoder network, a hidden Markov model (HMM), and a generative component: after dividing the signal into overlapping frames and performing a fast Fourier transform, MindReader trains an autoencoder neural network for dimensionality reduction and compact representation of different frequency patterns for each frame. Next, we processed the temporal patterns using a HMM, while a third and generative component hypothesized and characterized the different phases that were then fed back to the HMM. MindReader then automatically generates labels that the physician can interpret as pathological and non-pathological phases, thus effectively reducing the search space for trained personnel. We evaluated MindReader's predictive performance on 686 recordings, encompassing more than 980 h from the publicly available Physionet database. Compared to manual annotations, MindReader identified 197 of 198 epileptic events (99.45%), and is, as such, a highly sensitive method, which is a prerequisite for clinical use.

SumStatsRehab: an efficient algorithm for GWAS summary statistics assessment and restoration.

BACKGROUND: Generating polygenic risk scores for diseases and complex traits requires high quality GWAS summary statistic files. Often, these files can be difficult to acquire either as a result of unshared or incomplete data. To date, bioinformatics tools which focus on restoring missing columns containing identification and association data are limited, which has the potential to increase the number of usable GWAS summary statistics files. RESULTS: SumStatsRehab was able to restore rsID, effect/other alleles, chromosome, base pair position, effect allele frequencies, beta, standard error, and p-values to a better extent than any other currently available tool, with minimal loss. CONCLUSIONS: SumStatsRehab offers a unique tool utilizing both functional programming and pipeline-like architecture, allowing users to generate accurate data restorations for incomplete summary statistics files. This in turn, increases the number of usable GWAS summary statistics files, which may be invaluable for less researched health traits.

Flexible Machine Learning Algorithms for Clinical Gait Assessment Tools.

The current gold standard of gait diagnostics is dependent on large, expensive motion-capture laboratories and highly trained clinical and technical staff. Wearable sensor systems combined with machine learning may help to improve the accessibility of objective gait assessments in a broad clinical context. However, current algorithms lack flexibility and require large training datasets with tedious manual labelling of data. The current study tests the validity of a novel machine learning algorithm for automated gait partitioning of laboratory-based and sensor-based gait data. The developed artificial intelligence tool was used in patients with a central neurological lesion and severe gait impairments. To build the novel algorithm, 2% and 3% of the entire dataset (567 and 368 steps in total, respectively) were required for assessments with laboratory equipment and inertial measurement units. The mean errors of machine learning-based gait partitions were 0.021 s for the laboratory-based datasets and 0.034 s for the sensor-based datasets. Combining reinforcement learning with a deep neural network allows significant reduction in the size of the training datasets to <5%. The low number of required training data provides end-users with a high degree of flexibility. Non-experts can easily adjust the developed algorithm and modify the training library depending on the measurement system and clinical population.

Evolution of Darwin's finches and their beaks revealed by genome sequencing.

Darwin's finches, inhabiting the Galápagos archipelago and Cocos Island, constitute an iconic model for studies of speciation and adaptive evolution. Here we report the results of whole-genome re-sequencing of 120 individuals representing all of the Darwin's finch species and two close relatives. Phylogenetic analysis reveals important discrepancies with the phenotype-based taxonomy. We find extensive evidence for interspecific gene flow throughout the radiation. Hybridization has given rise to species of mixed ancestry. A 240 kilobase haplotype encompassing the ALX1 gene that encodes a transcription factor affecting craniofacial development is strongly associated with beak shape diversity across Darwin's finch species as well as within the medium ground finch (Geospiza fortis), a species that has undergone rapid evolution of beak shape in response to environmental changes. The ALX1 haplotype has contributed to diversification of beak shapes among the Darwin's finches and, thereby, to an expanded utilization of food resources.

Functional and evolutionary genomic inferences in Populus through genome and population sequencing of American and European aspen.

The Populus genus is one of the major plant model systems, but genomic resources have thus far primarily been available for poplar species, and primarily Populus trichocarpa (Torr. & Gray), which was the first tree with a whole-genome assembly. To further advance evolutionary and functional genomic analyses in Populus, we produced genome assemblies and population genetics resources of two aspen species, Populus tremula L. and Populus tremuloides Michx. The two aspen species have distributions spanning the Northern Hemisphere, where they are keystone species supporting a wide variety of dependent communities and produce a diverse array of secondary metabolites. Our analyses show that the two aspens share a similar genome structure and a highly conserved gene content with P. trichocarpa but display substantially higher levels of heterozygosity. Based on population resequencing data, we observed widespread positive and negative selection acting on both coding and noncoding regions. Furthermore, patterns of genetic diversity and molecular evolution in aspen are influenced by a number of features, such as expression level, coexpression network connectivity, and regulatory variation. To maximize the community utility of these resources, we have integrated all presented data within the PopGenIE web resource (PopGenIE.org).

Investigation of the host transcriptional response to intracellular bacterial infection using Dictyostelium discoideum as a host model.

BACKGROUND: During infection by intracellular pathogens, a highly complex interplay occurs between the infected cell trying to degrade the invader and the pathogen which actively manipulates the host cell to enable survival and proliferation. Many intracellular pathogens pose important threats to human health and major efforts have been undertaken to better understand the host-pathogen interactions that eventually determine the outcome of the infection. Over the last decades, the unicellular eukaryote Dictyostelium discoideum has become an established infection model, serving as a surrogate macrophage that can be infected with a wide range of intracellular pathogens. In this study, we use high-throughput RNA-sequencing to analyze the transcriptional response of D. discoideum when infected with Mycobacterium marinum and Legionella pneumophila. The results were compared to available data from human macrophages. RESULTS: The majority of the transcriptional regulation triggered by the two pathogens was found to be unique for each bacterial challenge. Hallmark transcriptional signatures were identified for each infection, e.g. induction of endosomal sorting complexes required for transport (ESCRT) and autophagy genes in response to M. marinum and inhibition of genes associated with the translation machinery and energy metabolism in response to L. pneumophila. However, a common response to the pathogenic bacteria was also identified, which was not induced by non-pathogenic food bacteria. Finally, comparison with available data sets of regulation in human monocyte derived macrophages shows that the elicited response in D. discoideum is in many aspects similar to what has been observed in human immune cells in response to Mycobacterium tuberculosis and L. pneumophila. CONCLUSIONS: Our study presents high-throughput characterization of D. discoideum transcriptional response to intracellular pathogens using RNA-seq. We demonstrate that the transcriptional response is in essence distinct to each pathogen and that in many cases, the corresponding regulation is recapitulated in human macrophages after infection by mycobacteria and L. pneumophila. This indicates that host-pathogen interactions are evolutionary conserved, derived from the early interactions between free-living phagocytic cells and bacteria. Taken together, our results strengthen the use of D. discoideum as a general infection model.

ACES: a machine learning toolbox for clustering analysis and visualization.

BACKGROUND: Studies that aim at explaining phenotypes or disease susceptibility by genetic or epigenetic variants often rely on clustering methods to stratify individuals or samples. While statistical associations may point at increased risk for certain parts of the population, the ultimate goal is to make precise predictions for each individual. This necessitates tools that allow for the rapid inspection of each data point, in particular to find explanations for outliers. RESULTS: ACES is an integrative cluster- and phenotype-browser, which implements standard clustering methods, as well as multiple visualization methods in which all sample information can be displayed quickly. In addition, ACES can automatically mine a list of phenotypes for cluster enrichment, whereby the number of clusters and their boundaries are estimated by a novel method. For visual data browsing, ACES provides a 2D or 3D PCA or Heat Map view. ACES is implemented in Java, with a focus on a user-friendly, interactive, graphical interface. CONCLUSIONS: ACES has been proven an invaluable tool for analyzing large, pre-filtered DNA methylation data sets and RNA-Sequencing data, due to its ease to link molecular markers to complex phenotypes. The source code is available from https://github.com/GrabherrGroup/ACES .

Comparative omics and feeding manipulations in chicken indicate a shift of the endocrine role of visceral fat towards reproduction.

BACKGROUND: The mammalian adipose tissue plays a central role in energy-balance control, whereas the avian visceral fat hardly expresses leptin, the key adipokine in mammals. Therefore, to assess the endocrine role of adipose tissue in birds, we compared the transcriptome and proteome between two metabolically different types of chickens, broilers and layers, bred towards efficient meat and egg production, respectively. RESULTS: Broilers and layer hens, grown up to sexual maturation under free-feeding conditions, differed 4.0-fold in weight and 1.6-fold in ovarian-follicle counts, yet the relative accumulation of visceral fat was comparable. RNA-seq and mass-spectrometry (MS) analyses of visceral fat revealed differentially expressed genes between broilers and layers, 1106 at the mRNA level (FDR ≤ 0.05), and 203 at the protein level (P ≤ 0.05). In broilers, Ingenuity Pathway Analysis revealed activation of the PTEN-pathway, and in layers increased response to external signals. The expression pattern of genes encoding fat-secreted proteins in broilers and layers was characterized in the RNA-seq and MS data, as well as by qPCR on visceral fat under free feeding and 24 h-feed deprivation. This characterization was expanded using available RNA-seq data of tissues from red junglefowl, and of visceral fat from broilers of different types. These comparisons revealed expression of new adipokines and secreted proteins (LCAT, LECT2, SERPINE2, SFTP1, ZP1, ZP3, APOV1, VTG1 and VTG2) at the mRNA and/or protein levels, with dynamic gene expression patterns in the selected chicken lines (except for ZP1; FDR/P ≤ 0.05) and feed deprivation (NAMPT, SFTPA1 and ZP3) (P ≤ 0.05). In contrast, some of the most prominent adipokines in mammals, leptin, TNF, IFNG, and IL6 were expressed at a low level (FPKM/RPKM< 1) and did not show differential mRNA expression neither between broiler and layer lines nor between fed vs. feed-deprived chickens. CONCLUSIONS: Our study revealed that RNA and protein expression in visceral fat changes with selective breeding, suggesting endocrine roles of visceral fat in the selected phenotypes. In comparison to gene expression in visceral fat of mammals, our findings points to a more direct cross talk of the chicken visceral fat with the reproductive system and lower involvement in the regulation of appetite, inflammation and insulin resistance.

Global characterization of the Dicer-like protein DrnB roles in miRNA biogenesis in the social amoeba Dictyostelium discoideum.

Micro (mi)RNAs regulate gene expression in many eukaryotic organisms where they control diverse biological processes. Their biogenesis, from primary transcripts to mature miRNAs, have been extensively characterized in animals and plants, showing distinct differences between these phylogenetically distant groups of organisms. However, comparably little is known about miRNA biogenesis in organisms whose evolutionary position is placed in between plants and animals and/or in unicellular organisms. Here, we investigate miRNA maturation in the unicellular amoeba Dictyostelium discoideum, belonging to Amoebozoa, which branched out after plants but before animals. High-throughput sequencing of small RNAs and poly(A)-selected RNAs demonstrated that the Dicer-like protein DrnB is required, and essentially specific, for global miRNA maturation in D. discoideum. Our RNA-seq data also showed that longer miRNA transcripts, generally preceded by a T-rich putative promoter motif, accumulate in a drnB knock-out strain. For two model miRNAs we defined the transcriptional start sites (TSSs) of primary (pri)-miRNAs and showed that they carry the RNA polymerase II specific m7G-cap. The generation of the 3'-ends of these pri-miRNAs differs, with pri-mir-1177 reading into the downstream gene, and pri-mir-1176 displaying a distinct end. This 3´-end is processed to shorter intermediates, stabilized in DrnB-depleted cells, of which some carry a short oligo(A)-tail. Furthermore, we identified 10 new miRNAs, all DrnB dependent and developmentally regulated. Thus, the miRNA machinery in D. discoideum shares features with both plants and animals, which is in agreement with its evolutionary position and perhaps also an adaptation to its complex lifestyle: unicellular growth and multicellular development.

The genomic basis of adaptive evolution in threespine sticklebacks.

Marine stickleback fish have colonized and adapted to thousands of streams and lakes formed since the last ice age, providing an exceptional opportunity to characterize genomic mechanisms underlying repeated ecological adaptation in nature. Here we develop a high-quality reference genome assembly for threespine sticklebacks. By sequencing the genomes of twenty additional individuals from a global set of marine and freshwater populations, we identify a genome-wide set of loci that are consistently associated with marine-freshwater divergence. Our results indicate that reuse of globally shared standing genetic variation, including chromosomal inversions, has an important role in repeated evolution of distinct marine and freshwater sticklebacks, and in the maintenance of divergent ecotypes during early stages of reproductive isolation. Both coding and regulatory changes occur in the set of loci underlying marine-freshwater evolution, but regulatory changes appear to predominate in this well known example of repeated adaptive evolution in nature.

microTaboo: a general and practical solution to the k-disjoint problem.

BACKGROUND: A common challenge in bioinformatics is to identify short sub-sequences that are unique in a set of genomes or reference sequences, which can efficiently be achieved by k-mer (k consecutive nucleotides) counting. However, there are several areas that would benefit from a more stringent definition of "unique", requiring that these sub-sequences of length W differ by more than k mismatches (i.e. a Hamming distance greater than k) from any other sub-sequence, which we term the k-disjoint problem. Examples include finding sequences unique to a pathogen for probe-based infection diagnostics; reducing off-target hits for re-sequencing or genome editing; detecting sequence (e.g. phage or viral) insertions; and multiple substitution mutations. Since both sensitivity and specificity are critical, an exhaustive, yet efficient solution is desirable. RESULTS: We present microTaboo, a method that allows for efficient and extensive sequence mining of unique (k-disjoint) sequences of up to 100 nucleotides in length. On a number of simulated and real data sets ranging from microbe- to mammalian-size genomes, we show that microTaboo is able to efficiently find all sub-sequences of a specified length W that do not occur within a threshold of k mismatches in any other sub-sequence. We exemplify that microTaboo has many practical applications, including point substitution detection, sequence insertion detection, padlock probe target search, and candidate CRISPR target mining. CONCLUSIONS: microTaboo implements a solution to the k-disjoint problem in an alignment- and assembly free manner. microTaboo is available for Windows, Mac OS X, and Linux, running Java 7 and higher, under the GNU GPLv3 license, at: https://MohammedAlJaff.github.io/microTaboo.

Evolution of the p53-MDM2 pathway.

BACKGROUND: The p53 signalling pathway, which controls cell fate, has been extensively studied due to its prominent role in tumor development. The pathway includes the tumor supressor protein p53, its vertebrate paralogs p63 and p73, and their negative regulators MDM2 and MDM4. The p53/p63/p73-MDM system is ancient and can be traced in all extant animal phyla. Despite this, correct phylogenetic trees including both vertebrate and invertebrate species of the p53/p63/p73 and MDM families have not been published. RESULTS: Here, we have examined the evolution of the p53/p63/p73 protein family with particular focus on the p53/p63/p73 transactivation domain (TAD) and its co-evolution with the p53/p63/p73-binding domain (p53/p63/p73BD) of MDM2. We found that the TAD and p53/p63/p73BD share a strong evolutionary connection. If one of the domains of the protein is lost in a phylum, then it seems very likely to be followed by loss of function by the other domain as well, and due to the loss of function it is likely to eventually disappear. By focusing our phylogenetic analysis to p53/p63/p73 and MDM proteins from phyla that retain the interaction domains TAD and p53/p63/p73BD, we built phylogenetic trees of p53/p63/p73 and MDM based on both vertebrate and invertebrate species. The trees follow species evolution and contain a total number of 183 and 98 species for p53/p63/p73 and MDM, respectively. We also demonstrate that the p53/p63/p73 and MDM families result from whole genome duplications. CONCLUSIONS: The signaling pathway of the TAD and p53/p63/p73BD in p53/p63/p73 and MDM, respectively, dates back to early metazoan time and has since then tightly co-evolved, or disappeared in distinct lineages.

PiiL: visualization of DNA methylation and gene expression data in gene pathways.

BACKGROUND: DNA methylation is a major mechanism involved in the epigenetic state of a cell. It has been observed that the methylation status of certain CpG sites close to or within a gene can directly affect its expression, either by silencing or, in some cases, up-regulating transcription. However, a vertebrate genome contains millions of CpG sites, all of which are potential targets for methylation, and the specific effects of most sites have not been characterized to date. To study the complex interplay between methylation status, cellular programs, and the resulting phenotypes, we present PiiL, an interactive gene expression pathway browser, facilitating analyses through an integrated view of methylation and expression on multiple levels. RESULTS: PiiL allows for specific hypothesis testing by quickly assessing pathways or gene networks, where the data is projected onto pathways that can be downloaded directly from the online KEGG database. PiiL provides a comprehensive set of analysis features that allow for quick and specific pattern searches. Individual CpG sites and their impact on host gene expression, as well as the impact on other genes present in the regulatory network, can be examined. To exemplify the power of this approach, we analyzed two types of brain tumors, Glioblastoma multiform and lower grade gliomas. CONCLUSION: At a glance, we could confirm earlier findings that the predominant methylation and expression patterns separate perfectly by mutations in the IDH genes, rather than by histology. We could also infer the IDH mutation status for samples for which the genotype was not known. By applying different filtering methods, we show that a subset of CpG sites exhibits consistent methylation patterns, and that the status of sites affect the expression of key regulator genes, as well as other genes located downstream in the same pathways. PiiL is implemented in Java with focus on a user-friendly graphical interface. The source code is available under the GPL license from https://github.com/behroozt/PiiL.git .

Interactions of Freshwater Cyanobacteria with Bacterial Antagonists.

Cyanobacterial and algal mass development, or blooms, have severe effects on freshwater and marine systems around the world. Many of these phototrophs produce a variety of potent toxins, contribute to oxygen depletion, and affect water quality in several ways. Coexisting antagonists, such as cyanolytic bacteria, hold the potential to suppress, or even terminate, such blooms, yet the nature of this interaction is not well studied. We isolated 31 cyanolytic bacteria affiliated with the genera Pseudomonas, Stenotrophomonas, Acinetobacter, and Delftia from three eutrophic freshwater lakes in Sweden and selected four phylogenetically diverse bacterial strains with strong-to-moderate lytic activity. To characterize their functional responses to the presence of cyanobacteria, we performed RNA sequencing (RNA-Seq) experiments on coculture incubations, with an initial predator-prey ratio of 1:1. Genes involved in central cellular pathways, stress-related heat or cold shock proteins, and antitoxin genes were highly expressed in both heterotrophs and cyanobacteria. Heterotrophs in coculture expressed genes involved in cell motility, signal transduction, and putative lytic activity. l,d-Transpeptidase was the only significantly upregulated lytic gene in Stenotrophomonas rhizophila EK20. Heterotrophs also shifted their central metabolism from the tricarboxylic acid cycle to the glyoxylate shunt. Concurrently, cyanobacteria clearly show contrasting antagonistic interactions with the four tested heterotrophic strains, which is also reflected in the physical attachment to their cells. In conclusion, antagonistic interactions with cyanobacteria were initiated within 24 h, and expression profiles suggest varied responses for the different cyanobacteria and studied cyanolytes.IMPORTANCE Here, we present how gene expression profiles can be used to reveal interactions between bloom-forming freshwater cyanobacteria and antagonistic heterotrophic bacteria. Species-specific responses in both heterotrophs and cyanobacteria were identified. The study contributes to a better understanding of the interspecies cellular interactions underpinning the persistence and collapse of cyanobacterial blooms.

The genome of the green anole lizard and a comparative analysis with birds and mammals.

The evolution of the amniotic egg was one of the great evolutionary innovations in the history of life, freeing vertebrates from an obligatory connection to water and thus permitting the conquest of terrestrial environments. Among amniotes, genome sequences are available for mammals and birds, but not for non-avian reptiles. Here we report the genome sequence of the North American green anole lizard, Anolis carolinensis. We find that A. carolinensis microchromosomes are highly syntenic with chicken microchromosomes, yet do not exhibit the high GC and low repeat content that are characteristic of avian microchromosomes. Also, A. carolinensis mobile elements are very young and diverse-more so than in any other sequenced amniote genome. The GC content of this lizard genome is also unusual in its homogeneity, unlike the regionally variable GC content found in mammals and birds. We describe and assign sequence to the previously unknown A. carolinensis X chromosome. Comparative gene analysis shows that amniote egg proteins have evolved significantly more rapidly than other proteins. An anole phylogeny resolves basal branches to illuminate the history of their repeated adaptive radiations.

Combinatorial identification of DNA methylation patterns over age in the human brain.

BACKGROUND: DNA methylation plays a key role in developmental processes, which is reflected in changing methylation patterns at specific CpG sites over the lifetime of an individual. The underlying mechanisms are complex and possibly affect multiple genes or entire pathways. RESULTS: We applied a multivariate approach to identify combinations of CpG sites that undergo modifications when transitioning between developmental stages. Monte Carlo feature selection produced a list of ranked and statistically significant CpG sites, while rule-based models allowed for identifying particular methylation changes in these sites. Our rule-based classifier reports combinations of CpG sites, together with changes in their methylation status in the form of easy-to-read IF-THEN rules, which allows for identification of the genes associated with the underlying sites. CONCLUSION: We utilized machine learning and statistical methods to discretize decision class (age) values to get a general pattern of methylation changes over the lifespan. The CpG sites present in the significant rules were annotated to genes involved in brain formation, general development, as well as genes linked to cancer and Alzheimer's disease.

Whiteboard: a framework for the programmatic visualization of complex biological analyses.

UNLABELLED: Whiteboard is a class library implemented in C++ that enables visualization to be tightly coupled with computation when analyzing large and complex datasets. AVAILABILITY AND IMPLEMENTATION: the C++ source code, coding samples and documentation are freely available under the Lesser General Public License from http://whiteboard-class.sourceforge.net/.

Comparative genomics reveals mobile pathogenicity chromosomes in Fusarium.

Fusarium species are among the most important phytopathogenic and toxigenic fungi. To understand the molecular underpinnings of pathogenicity in the genus Fusarium, we compared the genomes of three phenotypically diverse species: Fusarium graminearum, Fusarium verticillioides and Fusarium oxysporum f. sp. lycopersici. Our analysis revealed lineage-specific (LS) genomic regions in F. oxysporum that include four entire chromosomes and account for more than one-quarter of the genome. LS regions are rich in transposons and genes with distinct evolutionary profiles but related to pathogenicity, indicative of horizontal acquisition. Experimentally, we demonstrate the transfer of two LS chromosomes between strains of F. oxysporum, converting a non-pathogenic strain into a pathogen. Transfer of LS chromosomes between otherwise genetically isolated strains explains the polyphyletic origin of host specificity and the emergence of new pathogenic lineages in F. oxysporum. These findings put the evolution of fungal pathogenicity into a new perspective.

Broad-scale phylogenomics provides insights into retrovirus-host evolution.

Genomic data provide an excellent resource to improve understanding of retrovirus evolution and the complex relationships among viruses and their hosts. In conjunction with broad-scale in silico screening of vertebrate genomes, this resource offers an opportunity to complement data on the evolution and frequency of past retroviral spread and so evaluate future risks and limitations for horizontal transmission between different host species. Here, we develop a methodology for extracting phylogenetic signal from large endogenous retrovirus (ERV) datasets by collapsing information to facilitate broad-scale phylogenomics across a wide sample of hosts. Starting with nearly 90,000 ERVs from 60 vertebrate host genomes, we construct phylogenetic hypotheses and draw inferences regarding the designation, host distribution, origin, and transmission of the Gammaretrovirus genus and associated class I ERVs. Our results uncover remarkable depths in retroviral sequence diversity, supported within a phylogenetic context. This finding suggests that current infectious exogenous retrovirus diversity may be underestimated, adding credence to the possibility that many additional exogenous retroviruses may remain to be discovered in vertebrate taxa. We demonstrate a history of frequent horizontal interorder transmissions from a rodent reservoir and suggest that rats may have acted as important overlooked facilitators of gammaretrovirus spread across diverse mammalian hosts. Together, these results demonstrate the promise of the methodology used here to analyze large ERV datasets and improve understanding of retroviral evolution and diversity for utilization in wider applications.