SARS-CoV-2 transmission dynamics in Belarus revealed by genomic and incidence data analysis.

Since the emergence of COVID-19, a series of non-pharmaceutical interventions (NPIs) has been implemented by governments and public health authorities world-wide to control and curb the ongoing pandemic spread. From that perspective, Belarus is one of a few countries with a relatively modern healthcare system, where much narrower NPIs have been put in place. Given the uniqueness of this Belarusian experience, the understanding its COVID-19 epidemiological dynamics is essential not only for the local assessment, but also for a better insight into the impact of different NPI strategies globally. In this work, we integrate genomic epidemiology and surveillance methods to investigate the emergence and spread of SARS-CoV-2 in the country. The observed Belarusian SARS-CoV-2 genetic diversity originated from at least eighteen separate introductions, at least five of which resulted in on-going domestic transmissions. The introduction sources represent a wide variety of regions, although the proportion of regional virus introductions and exports from/to geographical neighbors appears to be higher than for other European countries. Phylodynamic analysis indicates a moderate reduction in the effective reproductive number ℛ e after the introduction of limited NPIs, with the reduction magnitude generally being lower than for countries with large-scale NPIs. On the other hand, the estimate of the Belarusian ℛ e at the early epidemic stage is comparable with this number for the neighboring ex-USSR country of Ukraine, where much broader NPIs have been implemented. The actual number of cases by the end of May, 2020 was predicted to be 2-9 times higher than the detected number of cases.

SARS-CoV-2 transmission dynamics in Belarus in 2020 revealed by genomic and incidence data analysis.

Background: Non-pharmaceutical interventions (NPIs) have been implemented worldwide to curb COVID-19 spread. Belarus is a rare case of a country with a relatively modern healthcare system, where highly limited NPIs have been enacted. Thus, investigation of Belarusian COVID-19 dynamics is essential for the local and global assessment of the impact of NPI strategies. Methods: We integrate genomic epidemiology and surveillance methods to investigate the spread of SARS-CoV-2 in Belarus in 2020. We utilize phylodynamics, phylogeography, and probabilistic bias inference to study the virus import and export routes, the dynamics of the effective reproduction number, and the incidence of SARS-CoV-2 infection. Results: Here we show that the estimated cumulative number of infections by June 2020 exceeds the confirmed case number by a factor of ~4 (95% confidence interval (2; 9)). Intra-country SARS-CoV-2 genomic diversity originates from at least 18 introductions from different regions, with a high proportion of regional transmissions. Phylodynamic analysis indicates a moderate reduction of the effective reproductive number after the introduction of limited NPIs, but its magnitude is lower than for developed countries with large-scale NPIs. On the other hand, the effective reproduction number estimate is comparable with that for the neighboring Ukraine, where NPIs were broader. Conclusions: The example of Belarus demonstrates how countries with relatively low outward population mobility continue to be integral parts of the global epidemiological environment. Comparison of the effective reproduction number dynamics for Belarus and other countries reveals the effect of different NPI strategies but also emphasizes the role of regional Eastern European sociodemographic factors in the virus spread.

Recurrent horizontal transfer identifies mitochondrial positive selection in a transmissible cancer.

Autonomous replication and segregation of mitochondrial DNA (mtDNA) creates the potential for evolutionary conflict driven by emergence of haplotypes under positive selection for 'selfish' traits, such as replicative advantage. However, few cases of this phenomenon arising within natural populations have been described. Here, we survey the frequency of mtDNA horizontal transfer within the canine transmissible venereal tumour (CTVT), a contagious cancer clone that occasionally acquires mtDNA from its hosts. Remarkably, one canine mtDNA haplotype, A1d1a, has repeatedly and recently colonised CTVT cells, recurrently replacing incumbent CTVT haplotypes. An A1d1a control region polymorphism predicted to influence transcription is fixed in the products of an A1d1a recombination event and occurs somatically on other CTVT mtDNA backgrounds. We present a model whereby 'selfish' positive selection acting on a regulatory variant drives repeated fixation of A1d1a within CTVT cells.

Somatic evolution and global expansion of an ancient transmissible cancer lineage.

The canine transmissible venereal tumor (CTVT) is a cancer lineage that arose several millennia ago and survives by "metastasizing" between hosts through cell transfer. The somatic mutations in this cancer record its phylogeography and evolutionary history. We constructed a time-resolved phylogeny from 546 CTVT exomes and describe the lineage's worldwide expansion. Examining variation in mutational exposure, we identify a highly context-specific mutational process that operated early in the cancer's evolution but subsequently vanished, correlate ultraviolet-light mutagenesis with tumor latitude, and describe tumors with heritable hyperactivity of an endogenous mutational process. CTVT displays little evidence of ongoing positive selection, and negative selection is detectable only in essential genes. We illustrate how long-lived clonal organisms capture changing mutagenic environments, and reveal that neutral genetic drift is the dominant feature of long-term cancer evolution.

Inference of genetic relatedness between viral quasispecies from sequencing data.

BACKGROUND: RNA viruses such as HCV and HIV mutate at extremely high rates, and as a result, they exist in infected hosts as populations of genetically related variants. Recent advances in sequencing technologies make possible to identify such populations at great depth. In particular, these technologies provide new opportunities for inference of relatedness between viral samples, identification of transmission clusters and sources of infection, which are crucial tasks for viral outbreaks investigations. RESULTS: We present (i) an evolutionary simulation algorithm Viral Outbreak InferenCE (VOICE) inferring genetic relatedness, (ii) an algorithm MinDistB detecting possible transmission using minimal distances between intra-host viral populations and sizes of their relative borders, and (iii) a non-parametric recursive clustering algorithm Relatedness Depth (ReD) analyzing clusters' structure to infer possible transmissions and their directions. All proposed algorithms were validated using real sequencing data from HCV outbreaks. CONCLUSIONS: All algorithms are applicable to the analysis of outbreaks of highly heterogeneous RNA viruses. Our experimental validation shows that they can successfully identify genetic relatedness between viral populations, as well as infer transmission clusters and outbreak sources.

Inferring metabolic pathway activity levels from RNA-Seq data.

BACKGROUND: Assessing pathway activity levels is a plausible way to quantify metabolic differences between various conditions. This is usually inferred from microarray expression data. Wide availability of NGS technology has triggered a demand for bioinformatics tools capable of analyzing pathway activity directly from RNA-Seq data. In this paper we introduce XPathway, a set of tools that compares pathway activity analyzing mapping of contigs assembled from RNA-Seq reads to KEGG pathways. The XPathway analysis of pathway activity is based on expectation maximization and topological properties of pathway graphs. RESULTS: XPathway tools have been applied to RNA-Seq data from the marine bryozoan Bugula neritina with and without its symbiotic bacterium "Candidatus Endobugula sertula". We successfully identified several metabolic pathways with differential activity levels. The expression of enzymes from the identified pathways has been further validated through quantitative PCR (qPCR). CONCLUSIONS: Our results show that XPathway is able to detect and quantify the metabolic difference in two samples. The software is implemented in C, Python and shell scripting and is capable of running on Linux/Unix platforms. The source code and installation instructions are available at http://alan.cs.gsu.edu/NGS/?q=content/xpathway .

Mitochondrial genetic diversity, selection and recombination in a canine transmissible cancer.

Canine transmissible venereal tumour (CTVT) is a clonally transmissible cancer that originated approximately 11,000 years ago and affects dogs worldwide. Despite the clonal origin of the CTVT nuclear genome, CTVT mitochondrial genomes (mtDNAs) have been acquired by periodic capture from transient hosts. We sequenced 449 complete mtDNAs from a global population of CTVTs, and show that mtDNA horizontal transfer has occurred at least five times, delineating five tumour clades whose distributions track two millennia of dog global migration. Negative selection has operated to prevent accumulation of deleterious mutations in captured mtDNA, and recombination has caused occasional mtDNA re-assortment. These findings implicate functional mtDNA as a driver of CTVT global metastatic spread, further highlighting the important role of mtDNA in cancer evolution.

Computational framework for next-generation sequencing of heterogeneous viral populations using combinatorial pooling.

MOTIVATION: Next-generation sequencing (NGS) allows for analyzing a large number of viral sequences from infected patients, providing an opportunity to implement large-scale molecular surveillance of viral diseases. However, despite improvements in technology, traditional protocols for NGS of large numbers of samples are still highly cost and labor intensive. One of the possible cost-effective alternatives is combinatorial pooling. Although a number of pooling strategies for consensus sequencing of DNA samples and detection of SNPs have been proposed, these strategies cannot be applied to sequencing of highly heterogeneous viral populations. RESULTS: We developed a cost-effective and reliable protocol for sequencing of viral samples, that combines NGS using barcoding and combinatorial pooling and a computational framework including algorithms for optimal virus-specific pools design and deconvolution of individual samples from sequenced pools. Evaluation of the framework on experimental and simulated data for hepatitis C virus showed that it substantially reduces the sequencing costs and allows deconvolution of viral populations with a high accuracy. AVAILABILITY AND IMPLEMENTATION: The source code and experimental data sets are available at http://alan.cs.gsu.edu/NGS/?q=content/pooling.

Improved transcriptome quantification and reconstruction from RNA-Seq reads using partial annotations.

The paper addresses the problem of how to use RNA-Seq data for transcriptome reconstruction and quantification, as well as novel transcript discovery in partially annotated genomes. We present a novel annotation-guided general framework for transcriptome discovery, reconstruction and quantification in partially annotated genomes and compare it with existing annotation-guided and genome-guided transcriptome assembly methods. Our method, referred as Discovery and Reconstruction of Unannotated Transcripts (DRUT), can be used to enhance existing transcriptome assemblers, such as Cufflinks, as well as to accurately estimate the transcript frequencies. Empirical analysis on synthetic datasets confirms that Cufflinks enhanced by DRUT has superior quality of reconstruction and frequency estimation of transcripts.