ViPRA-Haplo: De Novo Reconstruction of Viral Populations Using Paired End Sequencing Data.

We present ViPRA-Haplo, a de novo strain-specific assembly workflow for reconstructing viral haplotypes in a viral population from paired-end next generation sequencing (NGS) data. The proposed Viral Path Reconstruction Algorithm (ViPRA) generates a subset of paths from a De Bruijn graph of reads using the pairing information of reads. The paths generated by ViPRA are an over-estimation of the true contigs. We propose two refinement methods to obtain an optimal set of contigs representing viral haplotypes. The first method clusters paths reconstructed by ViPRA using VSEARCH [1] based on sequence similarity, while the second method, MLEHaplo, generates a maximum likelihood estimate of viral populations. We evaluated our pipeline on both simulated and real viral quasispecies data from HIV (and real data from SARS-COV-2). Experimental results show that ViPRA-Haplo, although still an overestimation in the number of true contigs, outperforms the existing tool, PEHaplo, providing up to 9% better genome coverage on HIV real data. In addition, ViPRA-Haplo also retains higher diversity of the viral population as demonstrated by the presence of a higher percentage of contigs less than 1000 base pairs (bps), which also contain k-mers with counts less than 100 (representing rarer sequences), which are absent in PEHaplo. For SARS-CoV-2 sequencing data, ViPRA-Haplo reconstructs contigs that cover more than 90% of the reference genome and were able to validate known SARS-CoV-2 strains in the sequencing data.

Recombination Marks the Evolutionary Dynamics of a Recently Endogenized Retrovirus.

All vertebrate genomes have been colonized by retroviruses along their evolutionary trajectory. Although endogenous retroviruses (ERVs) can contribute important physiological functions to contemporary hosts, such benefits are attributed to long-term coevolution of ERV and host because germline infections are rare and expansion is slow, and because the host effectively silences them. The genomes of several outbred species including mule deer (Odocoileus hemionus) are currently being colonized by ERVs, which provides an opportunity to study ERV dynamics at a time when few are fixed. We previously established the locus-specific distribution of cervid ERV (CrERV) in populations of mule deer. In this study, we determine the molecular evolutionary processes acting on CrERV at each locus in the context of phylogenetic origin, genome location, and population prevalence. A mule deer genome was de novo assembled from short- and long-insert mate pair reads and CrERV sequence generated at each locus. We report that CrERV composition and diversity have recently measurably increased by horizontal acquisition of a new retrovirus lineage. This new lineage has further expanded CrERV burden and CrERV genomic diversity by activating and recombining with existing CrERV. Resulting interlineage recombinants then endogenize and subsequently expand. CrERV loci are significantly closer to genes than expected if integration were random and gene proximity might explain the recent expansion of one recombinant CrERV lineage. Thus, in mule deer, retroviral colonization is a dynamic period in the molecular evolution of CrERV that also provides a burst of genomic diversity to the host population.

Retroviral sero-reactivity in LGL leukaemia patients and family members.

T-cell large granular lymphocyte (T-LGL) leukaemia is characterized by a clonal proliferation of cytotoxic T cells and is frequently associated with rheumatoid arthritis. Sera from some LGL leukaemia patients react to a portion of the human T-cell leukaemia virus (HTLV-1/2) transmembrane envelope protein, BA21, although HTLV-1/2 infection is rare in LGL leukaemia patients. Here we show that family members, including spouses, of an LGL leukaemia patient had elevated LGL counts, BA21 reactivity and, additionally, recognition of HIV-1 gp41. Thus, both LGL leukaemia patients and clinically normal contacts sharing the same environment have evidence of exposure to a retrovirus.

Retrovirus insertion site analysis of LGL leukemia patient genomes.

BACKGROUND: Large granular lymphocyte (LGL) leukemia is an uncommon cancer characterized by sustained clonal proliferation of LGL cells. Antibodies reactive to retroviruses have been documented in the serum of patients with LGL leukemia. Culture or molecular approaches have to date not been successful in identifying a retrovirus. METHODS: Because a retrovirus must integrate into the genome of an infected cell, we focused our efforts on detecting a novel retrovirus integration site in the clonally expanded LGL cells. We present a new computational tool that uses long-insert mate pair sequence data to search the genome of LGL leukemia cells for retrovirus integration sites. We also utilize recently published methods to interrogate the status of polymorphic human endogenous retrovirus type K (HERV-K) provirus in patient genomes. RESULTS: Our data show that there are no new retrovirus insertions in LGL genomes of LGL leukemia patients. However, our insertion call tool did detect four HERV-K provirus integration sites that are polymorphic in the human population but absent from the human reference genome, hg19. To determine if the prevalence of these or other polymorphic proviral HERV-Ks differed between LGL leukemia patients and the general population, we used a recently developed tool that reports sites in the human genome occupied by a known proviral HERV-K. We report that there are significant differences in the number of polymorphic HERV-Ks in the genomes of LGL leukemia patients of European origin compared to individuals with European ancestry in the 1000 genomes (KGP) data. CONCLUSIONS: Our study confirms that the clonal expansion of LGL cells in LGL leukemia is not driven by the integration of a new infectious or endogenous retrovirus, although we do not rule out that these cells are responding to retroviral antigens produced in other cell types. However, our computational analyses revealed that the genomes of LGL leukemia patients carry a higher burden of polymorphic HERV-K proviruses compare to individuals from KGP of European ancestry. Our research emphasizes the merits of comprehensive genomic assessment of HERV-K in cancer samples and suggests that further analyses to determine contributions of HERV-K to LGL leukemia are warranted.

A computational framework to assess genome-wide distribution of polymorphic human endogenous retrovirus-K In human populations.

Human Endogenous Retrovirus type K (HERV-K) is the only HERV known to be insertionally polymorphic; not all individuals have a retrovirus at a specific genomic location. It is possible that HERV-Ks contribute to human disease because people differ in both number and genomic location of these retroviruses. Indeed viral transcripts, proteins, and antibody against HERV-K are detected in cancers, auto-immune, and neurodegenerative diseases. However, attempts to link a polymorphic HERV-K with any disease have been frustrated in part because population prevalence of HERV-K provirus at each polymorphic site is lacking and it is challenging to identify closely related elements such as HERV-K from short read sequence data. We present an integrated and computationally robust approach that uses whole genome short read data to determine the occupation status at all sites reported to contain a HERV-K provirus. Our method estimates the proportion of fixed length genomic sequence (k-mers) from whole genome sequence data matching a reference set of k-mers unique to each HERV-K locus and applies mixture model-based clustering of these values to account for low depth sequence data. Our analysis of 1000 Genomes Project Data (KGP) reveals numerous differences among the five KGP super-populations in the prevalence of individual and co-occurring HERV-K proviruses; we provide a visualization tool to easily depict the proportion of the KGP populations with any combination of polymorphic HERV-K provirus. Further, because HERV-K is insertionally polymorphic, the genome burden of known polymorphic HERV-K is variable in humans; this burden is lowest in East Asian (EAS) individuals. Our study identifies population-specific sequence variation for HERV-K proviruses at several loci. We expect these resources will advance research on HERV-K contributions to human diseases.

A random forest classifier for detecting rare variants in NGS data from viral populations.

We propose a random forest classifier for detecting rare variants from sequencing errors in Next Generation Sequencing (NGS) data from viral populations. The method utilizes counts of varying length of k-mers from the reads of a viral population to train a Random forest classifier, called MultiRes, that classifies k-mers as erroneous or rare variants. Our algorithm is rooted in concepts from signal processing and uses a frame-based representation of k-mers. Frames are sets of non-orthogonal basis functions that were traditionally used in signal processing for noise removal. We define discrete spatial signals for genomes and sequenced reads, and show that k-mers of a given size constitute a frame. We evaluate MultiRes on simulated and real viral population datasets, which consist of many low frequency variants, and compare it to the error detection methods used in correction tools known in the literature. MultiRes has 4 to 500 times less false positives k-mer predictions compared to other methods, essential for accurate estimation of viral population diversity and their de-novo assembly. It has high recall of the true k-mers, comparable to other error correction methods. MultiRes also has greater than 95% recall for detecting single nucleotide polymorphisms (SNPs) and fewer false positive SNPs, while detecting higher number of rare variants compared to other variant calling methods for viral populations. The software is available freely from the GitHub link https://github.com/raunaq-m/MultiRes.

Finding the Genomic Basis of Local Adaptation: Pitfalls, Practical Solutions, and Future Directions.

Uncovering the genetic and evolutionary basis of local adaptation is a major focus of evolutionary biology. The recent development of cost-effective methods for obtaining high-quality genome-scale data makes it possible to identify some of the loci responsible for adaptive differences among populations. Two basic approaches for identifying putatively locally adaptive loci have been developed and are broadly used: one that identifies loci with unusually high genetic differentiation among populations (differentiation outlier methods) and one that searches for correlations between local population allele frequencies and local environments (genetic-environment association methods). Here, we review the promises and challenges of these genome scan methods, including correcting for the confounding influence of a species' demographic history, biases caused by missing aspects of the genome, matching scales of environmental data with population structure, and other statistical considerations. In each case, we make suggestions for best practices for maximizing the accuracy and efficiency of genome scans to detect the underlying genetic basis of local adaptation. With attention to their current limitations, genome scan methods can be an important tool in finding the genetic basis of adaptive evolutionary change.

Separating Putative Pathogens from Background Contamination with Principal Orthogonal Decomposition: Evidence for Leptospira in the Ugandan Neonatal Septisome.

Neonatal sepsis (NS) is responsible for over 1 million yearly deaths worldwide. In the developing world, NS is often treated without an identified microbial pathogen. Amplicon sequencing of the bacterial 16S rRNA gene can be used to identify organisms that are difficult to detect by routine microbiological methods. However, contaminating bacteria are ubiquitous in both hospital settings and research reagents and must be accounted for to make effective use of these data. In this study, we sequenced the bacterial 16S rRNA gene obtained from blood and cerebrospinal fluid (CSF) of 80 neonates presenting with NS to the Mbarara Regional Hospital in Uganda. Assuming that patterns of background contamination would be independent of pathogenic microorganism DNA, we applied a novel quantitative approach using principal orthogonal decomposition to separate background contamination from potential pathogens in sequencing data. We designed our quantitative approach contrasting blood, CSF, and control specimens and employed a variety of statistical random matrix bootstrap hypotheses to estimate statistical significance. These analyses demonstrate that Leptospira appears present in some infants presenting within 48 h of birth, indicative of infection in utero, and up to 28 days of age, suggesting environmental exposure. This organism cannot be cultured in routine bacteriological settings and is enzootic in the cattle that often live in close proximity to the rural peoples of western Uganda. Our findings demonstrate that statistical approaches to remove background organisms common in 16S sequence data can reveal putative pathogens in small volume biological samples from newborns. This computational analysis thus reveals an important medical finding that has the potential to alter therapy and prevention efforts in a critically ill population.

Error correction and statistical analyses for intra-host comparisons of feline immunodeficiency virus diversity from high-throughput sequencing data.

BACKGROUND: Infection with feline immunodeficiency virus (FIV) causes an immunosuppressive disease whose consequences are less severe if cats are co-infected with an attenuated FIV strain (PLV). We use virus diversity measurements, which reflect replication ability and the virus response to various conditions, to test whether diversity of virulent FIV in lymphoid tissues is altered in the presence of PLV. Our data consisted of the 3' half of the FIV genome from three tissues of animals infected with FIV alone, or with FIV and PLV, sequenced by 454 technology. RESULTS: Since rare variants dominate virus populations, we had to carefully distinguish sequence variation from errors due to experimental protocols and sequencing. We considered an exponential-normal convolution model used for background correction of microarray data, and modified it to formulate an error correction approach for minor allele frequencies derived from high-throughput sequencing. Similar to accounting for over-dispersion in counts, this accounts for error-inflated variability in frequencies - and quite effectively reproduces empirically observed distributions. After obtaining error-corrected minor allele frequencies, we applied ANalysis Of VAriance (ANOVA) based on a linear mixed model and found that conserved sites and transition frequencies in FIV genes differ among tissues of dual and single infected cats. Furthermore, analysis of minor allele frequencies at individual FIV genome sites revealed 242 sites significantly affected by infection status (dual vs. single) or infection status by tissue interaction. All together, our results demonstrated a decrease in FIV diversity in bone marrow in the presence of PLV. Importantly, these effects were weakened or undetectable when error correction was performed with other approaches (thresholding of minor allele frequencies; probabilistic clustering of reads). We also queried the data for cytidine deaminase activity on the viral genome, which causes an asymmetric increase in G to A substitutions, but found no evidence for this host defense strategy. CONCLUSIONS: Our error correction approach for minor allele frequencies (more sensitive and computationally efficient than other algorithms) and our statistical treatment of variation (ANOVA) were critical for effective use of high-throughput sequencing data in understanding viral diversity. We found that co-infection with PLV shifts FIV diversity from bone marrow to lymph node and spleen.

Induction and characterization of a replication competent cervid endogenous gammaretrovirus (CrERV) from mule deer cells.

Endogenous retroviruses (ERVs) were acquired during evolution of their host organisms after infection and mendelian inheritance in the germline by their exogenous counterparts. The ERVs can spread in the host genome and in some cases they affect the host phenotype. The cervid endogenous gammaretrovirus (CrERV) is one of only a few well-defined examples of evolutionarily recent invasion of mammalian genome by retroviruses. Thousands of insertionally polymorphic CrERV integration sites have been detected in wild ranging mule deer (Odocoileus hemionus) host populations. Here, we describe for the first time induction of replication competent CrERV by cocultivation of deer and human cells. We characterize the physical properties and tropism of the induced virus. The genomic sequence of the induced virus is phylogenetically related to the evolutionarily young endogenous CrERVs described so far. We also describe the level of replication block of CrERV on deer cells and its capacity to establish superinfection interference.

Lineage diversification of pigeon paramyxovirus effect re-emergence potential in chickens.

Genotype VI-paramyxovirus (GVI-PMV1) is a major cause of epidemic Newcastle-like disease in Columbiformes. This genotype of avian paramyxovirus type 1 has diversified rapidly since its introduction into the US in 1982 resulting in two extant lineages, which have different population growth properties. Although some GVI-PMV1s replicate poorly in chickens, it is possible that variants with different replicative or pathogenic potential in chickens exist among the genetically-diverse GVI-PMV1s strains. To determine if variants of Columbiform GVI-PMV1 with different phylogenetic affiliations have distinct phenotypic properties in chickens, we investigated the replicative properties of 10 naturally circulating pigeon-derived isolates representing four subgroups of GVI-PMV1 in primary chicken lung epithelial cells and in chicken embryos. Our data demonstrate that GVI-PMV1 variants have different infection phenotypes in their chicken source host and that properties reflect subgroup affiliation. These subgroup replicative properties are consistent with observed dynamics of viral population growth.

The population history of endogenous retroviruses in mule deer (Odocoileus hemionus).

Mobile elements are powerful agents of genomic evolution and can be exceptionally informative markers for investigating species and population-level evolutionary history. While several studies have utilized retrotransposon-based insertional polymorphisms to resolve phylogenies, few population studies exist outside of humans. Endogenous retroviruses are LTR-retrotransposons derived from retroviruses that have become stably integrated in the host genome during past infections and transmitted vertically to subsequent generations. They offer valuable insight into host-virus co-evolution and a unique perspective on host evolutionary history because they integrate into the genome at a discrete point in time. We examined the evolutionary history of a cervid endogenous gammaretrovirus (CrERVγ) in mule deer (Odocoileus hemionus). We sequenced 14 CrERV proviruses (CrERV-in1 to -in14), and examined the prevalence and distribution of 13 proviruses in 262 deer among 15 populations from Montana, Wyoming, and Utah. CrERV absence in white-tailed deer (O. virginianus), identical 5' and 3' long terminal repeat (LTR) sequences, insertional polymorphism, and CrERV divergence time estimates indicated that most endogenization events occurred within the last 200000 years. Population structure inferred from CrERVs (F ST = 0.008) and microsatellites (θ = 0.01) was low, but significant, with Utah, northwestern Montana, and a Helena herd being particularly differentiated. Clustering analyses indicated regional structuring, and non-contiguous clustering could often be explained by known translocations. Cluster ensemble results indicated spatial localization of viruses, specifically in deer from northeastern and western Montana. This study demonstrates the utility of endogenous retroviruses to elucidate and provide novel insight into both ERV evolutionary history and the history of contemporary host populations.

The microbial spectrum of neonatal sepsis in Uganda: recovery of culturable bacteria in mother-infant pairs.

Neonatal sepsis in the developing world is incompletely characterized. We seek to characterize the microbial spectrum involved in sepsis and determine the role of maternal transmission by comparing organisms that can be cultured from septic newborn infants and their mothers. From 80 consecutive mother-infant pairs meeting clinical criteria for neonatal sepsis, we collected infant blood and spinal fluid, and maternal blood and vaginal specimens. Identifiable bacteria were recovered from the blood in 32.5% of infants, and from 2.5% of cerebrospinal fluid cultures, for a total of 35% recoverable putative causative agents. Bacteria recovered from vaginal specimens were not concordant with those recovered from infants. Similarly there was no concordance of bacteria recovered from blood and cerebrospinal fluid. We conclude that relying on traditional bacterial culture techniques does not adequately delineate the role of maternal versus environmental sources of neonatal sepsis in this setting. More sensitive molecular approaches will be needed to properly characterize the maternal and environmental microbial community involved in neonatal sepsis in such developing countries.

Mutant-bin: unsupervised haplotype estimation of viral population diversity without reference genome.

High genetic variability in viral populations plays an important role in disease progression, pathogenesis, and drug resistance. The last few years has seen significant progress in the development of methods for reconstruction of viral populations using data from next-generation sequencing technologies. These methods identify the differences between individual haplotypes by mapping the short reads to a reference genome. Much less has been published about resolving the population structure when a reference genome is lacking or is not well-defined, which severely limits the application of these new technologies to resolve virus population structure. We describe a computational framework, called Mutant-Bin, for clustering individual haplotypes in a viral population and determining their prevalence based on a set of deep sequencing reads. The main advantages of our method are that: (i) it enables determination of the population structure and haplotype frequencies when a reference genome is lacking; (ii) the method is unsupervised-the number of haplotypes does not have to be specified in advance; and (iii) it identifies the polymorphic sites that co-occur in a subset of haplotypes and the frequency with which they appear in the viral population. The method was evaluated on simulated reads with sequencing errors and 454 pyrosequencing reads from HIV samples. Our method clustered a high percentage of haplotypes with low false-positive rates, even at low genetic diversity.

Successful establishment and global dispersal of genotype VI avian paramyxovirus serotype 1 after cross species transmission.

The evolutionary history of avian paramyxovirus serotype 1 (PMV1), which includes the agents of Newcastle disease (ND), is characterized by a series of strain emergence events since viruses in this family were first recognized in the 1920s. Despite the importance of ND to the poultry industry, little is known about PMV1 strain emergence events and the subsequent dispersal and evolution of new strains. The genotype VI-PMV1 was first identified in the 1980s and has been named pigeon paramyxovirus-1 (PPMV1) because of unusual host specificity with Columbiformes (Collins et al., 1996); it has been responsible for panzootics in both chickens and pigeons during that time. Here, we used evolutionary analyses to characterize the emergence of this contemporary PMV1 lineage. We demonstrate that GVI-PMV1 arose through cross-species transmission events from Galliformes (i.e. chicken) to Columbiformes, and quickly established in pigeon populations. Our studies revealed a close association between the time of viral emergence and panzootic events of this virus. The virus appeared first in Southeastern Europe and quickly spread across the European continent, which became the epicenter for global virus dissemination. With new viral gene sequences, we show that GVI-PMV1 viruses currently circulating in North America resulted from multiple invasion events from Europe, one associated with an exotic European Columbiformes species, and that extant lineages have diversified locally. This study extends our understanding of successful viral emergence subsequent to cross-species transmission and dispersal patterns of newly emerged avian viruses, which may improve surveillance awareness and disease control of this and other important avian pathogens.

Anticipating the prevalence of avian influenza subtypes H9 and H5 in live-bird markets.

An ability to forecast the prevalence of specific subtypes of avian influenza viruses (AIV) in live-bird markets would facilitate greatly the implementation of preventative measures designed to minimize poultry losses and human exposure. The minimum requirement for developing predictive quantitative tools is surveillance data of AIV prevalence sampled frequently over several years. Recently, a 4-year time series of monthly sampling of hemagglutinin subtypes 1-13 in ducks, chickens and quail in live-bird markets in southern China has become available. We used these data to investigate whether a simple statistical model, based solely on historical data (variables such as the number of positive samples in host X of subtype Y time t months ago), could accurately predict prevalence of H5 and H9 subtypes in chickens. We also examined the role of ducks and quail in predicting prevalence in chickens within the market setting because between-species transmission is thought to occur within markets but has not been measured. Our best statistical models performed remarkably well at predicting future prevalence (pseudo-R(2) = 0.57 for H9 and 0.49 for H5), especially considering the multi-host, multi-subtype nature of AIVs. We did not find prevalence of H5/H9 in ducks or quail to be predictors of prevalence in chickens within the Chinese markets. Our results suggest surveillance protocols that could enable more accurate and timely predictive statistical models. We also discuss which data should be collected to allow the development of mechanistic models.

The origin of specificity by means of natural selection: evolved and nonhost resistance in host-pathogen interactions.

Most species seem to be completely resistant to most pathogens and parasites. This resistance has been called "nonhost resistance" because it is exhibited by species that are considered not to be part of the normal host range of the pathogen. A conceptual model is presented suggesting that failure of infection on nonhosts may be an incidental by-product of pathogen evolution leading to specialization on their source hosts. This model is contrasted with resistance that results from hosts evolving to resist challenge by their pathogens, either as a result of coevolution with a persistent pathogen or as the result of one-sided evolution by the host against pathogens that are not self-sustaining on those hosts. Distinguishing evolved from nonevolved resistance leads to contrasting predictions regarding the relationship between resistance and genetic distance. An analysis of cross-inoculation experiments suggests that the resistance is often the product of pathogen specialization. Understanding the contrasting evolutionary origins of resistance is critical for studies on the genetics and evolution of host-pathogen interactions in human, agricultural, and natural populations. Research on human infectious disease using animal models may often study resistances that have quite contrasting evolutionary origins, and therefore very different underlying genetic mechanisms.

Multiannual patterns of influenza A transmission in Chinese live bird market systems.

BACKGROUND: Avian influenza viruses (AIV) cause huge economic losses in poultry industries and pose a substantial threat to human health. However, predicting AIV epizootics and emergence in humans is confounded by insufficient empirical data on the ecology and dynamics of AIV in poultry systems. To address this gap, we quantified incidence patterns for 13 hemagglutinin subtypes of AIV using 6 years of surveillance data that were collected from ten different species of poultry and three different types of poultry holdings (contexts) - retail, wholesale, or farms. METHODS: We collected 42 646 samples in Shantou, China between 2000 and 2006. We screened samples for hemagglutinin subtypes 1-13 of AIV and Avian Paramyxovirus-type-1 (APMV-1) using monospecific antisera in hemagglutination inhibition tests. We analyzed the data to determine seasonality patterns, subtype-host, and subtype-subtype interactions as well as subtype bias in incidence in different contexts. RESULTS: H3, H6, H9, and APMV-1 were the most prevalent. No significant seasonality was found when all subtypes were considered together. For most AIV subtypes and APMV-1, there was subtype specificity for host, context, and coinfection partner. H5 showed the most generalized host usage pattern, followed by H9 and H6. CONCLUSION: Subtype-specific patterns because of host, context, and other subtypes suggest that risk assessments that exclude these details are likely inaccurate. Surveillance should include longitudinal sampling of multiple host species in multiple contexts. Quantitative models of control strategies must consider multiple subtypes, hosts, and source contexts to assess the effectiveness of interventions.

Polymorphic integrations of an endogenous gammaretrovirus in the mule deer genome.

Endogenous retroviruses constitute a significant genomic fraction in all mammalian species. Typically they are evolutionarily old and fixed in the host species population. Here we report on a novel endogenous gammaretrovirus (CrERVγ; for cervid endogenous gammaretrovirus) in the mule deer (Odocoileus hemionus) that is insertionally polymorphic among individuals from the same geographical location, suggesting that it has a more recent evolutionary origin. Using PCR-based methods, we identified seven CrERVγ proviruses and demonstrated that they show various levels of insertional polymorphism in mule deer individuals. One CrERVγ provirus was detected in all mule deer sampled but was absent from white-tailed deer, indicating that this virus originally integrated after the split of the two species, which occurred approximately one million years ago. There are, on average, 100 CrERVγ copies in the mule deer genome based on quantitative PCR analysis. A CrERVγ provirus was sequenced and contained intact open reading frames (ORFs) for three virus genes. Transcripts were identified covering the entire provirus. CrERVγ forms a distinct branch of the gammaretrovirus phylogeny, with the closest relatives of CrERVγ being endogenous gammaretroviruses from sheep and pig. We demonstrated that white-tailed deer (Odocoileus virginianus) and elk (Cervus canadensis) DNA contain proviruses that are closely related to mule deer CrERVγ in a conserved region of pol; more distantly related sequences can be identified in the genome of another member of the Cervidae, the muntjac (Muntiacus muntjak). The discovery of a novel transcriptionally active and insertionally polymorphic retrovirus in mammals could provide a useful model system to study the dynamic interaction between the host genome and an invading retrovirus.