scholarly journals Accelerated decline of genome heterogeneity in the SARS-CoV-2 coronavirus

2021 ◽  
Author(s):  
Jose L. Oliver ◽  
Pedro Bernaola-Galvan ◽  
Francisco Perfectti ◽  
Cristina Gomez-Martin ◽  
Miguel Verdu ◽  
...  
Keyword(s):  
Evolutionary Rate ◽  
Phylogenetic Signal ◽  
Strong Indication ◽  
High Quality ◽  
Human Host ◽  
Adaptive Process ◽  
Threefold Increase ◽  
Viral Adaptation ◽  
Genome Heterogeneity ◽  
Low Rate

In the brief time since the outbreak of the COVID 19 pandemic, and despite its proofreading mechanism, the SARS-CoV-2 coronavirus has accumulated a significant amount of genetic variability through recombination and mutation events. To test evolutionary trends that could inform us on the adaptive process of the virus to its human host, we summarize all this variability in the Sequence Compositional Complexity (SCC), a measure of genome heterogeneity that captures the mutational and recombinational changes accumulated by a nucleotide sequence along time. Despite the brief time elapsed, we detected many differences in the number and length of compositional domains, as well as in their nucleotide frequencies, in more than 12,000 high-quality coronavirus genomes from across the globe. These differences in SCC are phylogenetically structured, as revealed by significant phylogenetic signal. Phylogenetic ridge regression shows that SCC followed a generalized decreasing trend along the ongoing process of pathogen evolution. In contrast, SCC evolutionary rate increased with time, showing that it accelerates toward the present. In addition, a low rate set of genomes was detected in all the genome groups, suggesting the existence of a stepwise distribution of rates, a strong indication of selection in favor of different dominant strains. Coronavirus variants reveal an exacerbation of this trend: non-significant SCC regression, low phylogenetic signal and, concomitantly, a threefold increase in the evolutionary rate. Altogether, these results show an accelerated decline of genome heterogeneity along with the SARS CoV 2 pandemic expansion, a process that might be related to viral adaptation to the human host, perhaps paralleling the transformation of the current pandemic to epidemic.

scholarly journals Dating the Common Ancestor from an NCBI Tree of 83688 High-Quality and Full-Length SARS-CoV-2 Genomes

Viruses ◽  
2021 ◽  
Vol 13 (9) ◽  
pp. 1790
Author(s):  
Xuhua Xia
Keyword(s):  
Common Ancestor ◽  
Evolutionary Rate ◽  
Pearson Correlation ◽  
Sequence Divergence ◽  
Full Length ◽  
Recent Common Ancestor ◽  
High Quality ◽  
Most Recent Common Ancestor ◽  
Large Tree ◽  
Collection Time

All dating studies involving SARS-CoV-2 are problematic. Previous studies have dated the most recent common ancestor (MRCA) between SARS-CoV-2 and its close relatives from bats and pangolins. However, the evolutionary rate thus derived is expected to differ from the rate estimated from sequence divergence of SARS-CoV-2 lineages. Here, I present dating results for the first time from a large phylogenetic tree with 86,582 high-quality full-length SARS-CoV-2 genomes. The tree contains 83,688 genomes with full specification of collection time. Such a large tree spanning a period of about 1.5 years offers an excellent opportunity for dating the MRCA of the sampled SARS-CoV-2 genomes. The MRCA is dated 16 August 2019, with the evolutionary rate estimated to be 0.05526 mutations/genome/day. The Pearson correlation coefficient (r) between the root-to-tip distance (D) and the collection time (T) is 0.86295. The NCBI tree also includes 10 SARS-CoV-2 genomes isolated from cats, collected over roughly the same time span as human COVID-19 infection. The MRCA from these cat-derived SARS-CoV-2 is dated 30 July 2019, with r = 0.98464. While the dating method is well known, I have included detailed illustrations so that anyone can repeat the analysis and obtain the same dating results. With 16 August 2019 as the date of the MRCA of sampled SARS-CoV-2 genomes, archived samples from respiratory or digestive tracts collected around or before 16 August 2019, or those that are not descendants of the existing SARS-CoV-2 lineages, should be particularly valuable for tracing the origin of SARS-CoV-2.

scholarly journals Best practice for bio-waste collection as a prerequisite for high-quality compost

2021 ◽  
pp. 0734242X2110337
Author(s):  
Henning Friege ◽  
Yasmin Eger
Keyword(s):  
Population Density ◽  
Best Practice ◽  
Organic Waste ◽  
Public Awareness ◽  
Structured Interview ◽  
High Population Density ◽  
Waste Collection ◽  
Collection System ◽  
High Quality ◽  
Low Rate

Due to its high content of humic substances, compost from bio-waste improves the structure and fertility of soils serving also as a sink for CO2. But compost is also contaminated with numerous compounds, for example, plastics, glass particles, etc., mostly due to incorrect sorting by the waste producer, that is, households. The contamination even increases when covering areas of a high population density as is also evident from experience in Germany with a steadily increasing proportion of bio-waste. Only compost with high quality and minimum contamination is an acceptable fertilizer. A structured interview of experts investigated which measures or combinations of measures are best suitable to reduce the rate of misplaced materials in the organic waste. Only responsible persons were interviewed whose municipalities extensively collect separately bio-waste since years and have a low rate of unwanted materials. The questions focus on the identification of the misplacements according to their kind and quantity, the respective collection system, the regional statutes and their enforcement as well as the kind and extent of public awareness measures. The respective necessary measures are being discussed. This systemic approach can be transferred to other regions that intend to collect large quantities of bio-waste separately.

scholarly journals High-resolution genomic surveillance of 2014 ebolavirus using shared subclonal variants

2014 ◽  
Author(s):  
Kevin J Emmett ◽  
Albert K Lee ◽  
Hossein Khiabanian ◽  
Raul Rabadan
Keyword(s):  
Sierra Leone ◽  
Disease Transmission ◽  
Evolutionary Dynamics ◽  
Evolutionary Rate ◽  
Phylogenetic Signal ◽  
Founder Population ◽  
Effective Population ◽  
Phylogenetic Resolution ◽  
Analyze Data

Viral outbreaks, such as the 2014 ebolavirus, can spread rapidly and have complex evolutionary dynamics, including coinfection and bulk transmission of multiple viral populations. Genomic surveillance can be hindered when the spread of the outbreak exceeds the evolutionary rate, in which case consensus approaches will have limited resolution. Deep sequencing of infected patients can identify genomic variants present in intrahost populations at subclonal frequencies (i.e. <50%). Shared subclonal variants (SSVs) can provide additional phylogenetic resolution and inform about disease transmission patterns. Here, we use metrics from population genetics to analyze data from the 2014 ebolavirus outbreak in Sierra Leone and identify phylogenetic signal arising from SSVs. We use methods derived from information theory to measure a lower bound on transmission bottleneck size that is larger than one founder population, yet significantly smaller than the intrahost effective population. Our results demonstrate the important role of shared subclonal variants in genomic surveillance.

scholarly journals Evolutionarily stable gene clusters shed light on the common grounds of pathogenicity in the Acinetobacter calcoaceticus-baumanniicomplex

2022 ◽  
Author(s):  
Bardya Djahanschiri ◽  
Gisela Di Venanzio ◽  
Jesus S. Distel ◽  
Jennifer Breisch ◽  
Marius Alfred Dieckmann ◽  
...  
Keyword(s):  
Phylogenetic Signal ◽  
Functional Integration ◽  
Acinetobacter Calcoaceticus ◽  
Gene Clusters ◽  
Resistant Bacteria ◽  
Stable Gene ◽  
Last Common Ancestor ◽  
Human Host ◽  
Evolutionarily Stable ◽  
Shed Light

Nosocomial pathogens of the Acinetobacter calcoaceticus-baumannii (ACB) complex are a cautionary example for the world-wide spread of multi- and pan-drug resistant bacteria. Aiding the urgent demand for novel therapeutic targets, comparative genomics studies between pathogens and their apathogenic relatives shed light on the genetic basis of human-pathogen interaction. Yet, existing studies are limited in taxonomic scope, sensing of the phylogenetic signal, and resolution by largely analyzing genes isolated from their functional contexts. Here, we explored more than 3,000 Acinetobacter genomes in a phylogenomic framework integrating orthology-based phylogenetic profiling and micro-synteny conservation analyses. This allowed to delineate gene clusters in the type strain A. baumannii ATCC 19606 whose evolutionary conservation indicates a functional integration of the subsumed genes. These evolutionarily stable gene clusters (ESGCs) reveal metabolic pathways, transcriptional regulators residing next to their targets but also tie together sub-clusters with distinct functions to form higher-order functional modules. We shortlisted 150 ESGCs that either co-emerged with, or are found preferentially in, the pathogenic ACB clade. They unveil, at an unprecedented resolution, the genetic makeup that coincides with the manifestation of the pathogenic phenotype in the last common ancestor of the ACB clade. Key innovations are the remodeling of the regulatory-effector cascade connecting LuxR/LuxI quorum sensing via an intermediate messenger to biofilm formation, the extension of micronutrient scavenging systems, and the increase of metabolic flexibility by exploiting carbon sources that are provided by the human host. Specifically, we could show that only members of the ACB clade use kynurenine as a sole carbon and energy source, a substance produced by humans to fine-tune the antimicrobial innate immune response. In summary, this study provides a rich and unbiased set of novel testable hypotheses on how pathogenic Acinetobacter interact with and ultimately infect their human host. They disclose promising routes for future therapeutic strategies.

scholarly journals Phylogenetic Analysis Of SARS-CoV-2 In The First Months Since Its Emergence

2020 ◽  
Author(s):  
Matías J. Pereson ◽  
Laura Mojsiejczuk ◽  
Alfredo P. Martínez ◽  
Diego M. Flichman ◽  
Gabriel H. Garcia ◽  
...  
Keyword(s):  
Evolutionary Rate ◽  
Phylogenetic Signal ◽  
Essential Feature ◽  
Evolutionary Analysis ◽  
New Host ◽  
Viral Emergence ◽  
Genomic Regions ◽  
Virus Emergence ◽  
First Time

ABSTRACTDuring the first months of SARS-CoV-2 evolution in a new host, contrasting hypotheses have been proposed about the way the virus has evolved and diversified worldwide. The aim of this study was to perform a comprehensive evolutionary analysis to describe the human outbreak and the evolutionary rate of different genomic regions of SARS-CoV-2.The molecular evolution in nine genomic regions of SARS-CoV-2 was analyzed using three different approaches: phylogenetic signal assessment, emergence of amino acid substitutions, and Bayesian evolutionary rate estimation in eight successive fortnights since the virus emergence.All observed phylogenetic signals were very low and trees topologies were in agreement with those signals. However, after four months of evolution, it was possible to identify regions revealing an incipient viral lineages formation despite the low phylogenetic signal, since fortnight 3. Finally, the SARS-CoV-2 evolutionary rate for regions nsp3 and S, the ones presenting greater variability, was estimated to values of 1.37 × 10−3 and 2.19 × 10−3 substitution/site/year, respectively.In conclusion, results obtained in this work about the variable diversity of crucial viral regions and the determination of the evolutionary rate are consequently decisive to understand essential feature of viral emergence. In turn, findings may allow characterizing for the first time, the evolutionary rate of S protein that is crucial for vaccines development.

scholarly journals Lower statistical support with larger datasets: insights from the Ochrophyta radiation

2021 ◽  
Author(s):  
Arnaud Di Franco ◽  
Denis Baurain ◽  
Gernot Glöckner ◽  
Michael Melkonian ◽  
Hervé Philippe
Keyword(s):  
Evolutionary Rate ◽  
Phylogenetic Signal ◽  
Signal Extraction ◽  
Taxon Sampling ◽  
Sequence Evolution ◽  
Internal Branch ◽  
Statistical Support ◽  
Dataset Size ◽  
Fitting Model ◽  
Heterogeneous Size

AbstractIt is commonly assumed that increasing the number of characters has the potential to resolving radiations. We studied photosynthetic stramenopiles (Ochrophyta) using alignments of heterogeneous size and origin (6,762 sites for mitochondrion, 21,692 sites for plastid and 209,105 sites for nucleus). While statistical support for the relationships between the six major Ochrophyta lineages increases when comparing the mitochondrion and plastid trees, it decreases in the nuclear tree. Statistical support is not simply related to the dataset size but also to the quantity of phylogenetic signal available at each position and our ability to extract it. Here, we show that proper signal extraction is difficult to attain, as demonstrated by conflicting results obtained when varying taxon sampling. Even though the use of a better fitting model improved signal extraction and reduced the observed conflicts, the plastid dataset provided higher statistical support for the ochrophyte radiation than the larger nucleus dataset. We propose that the higher support observed in the plastid tree is due to an acceleration of the evolutionary rate in one short deep internal branch, implying that more phylogenetic signal per position is available to resolve the Ochrophyta radiation in the plastid than in the nuclear dataset. Our work therefore suggests that, in order to resolve radiations, beyond the obvious use of datasets with more positions, we need to continue developing models of sequence evolution that better extract the phylogenetic signal and design methods to search for genes/characters that contain more signal specifically for short internal branches.

Super-wideband fine spectrum quantization for low-rate high-quality MDCT coding mode of the 3GPP EVS codec

2015 ◽  
Author(s):  
Srikanth Nagisetty ◽  
Takuya Kawashima ◽  
Hiroyuki Ehara ◽  
Lasse Laaksonen ◽  
Hosang Sung ◽  
...  
Keyword(s):  
High Quality ◽  
Fine Spectrum ◽  
Coding Mode ◽  
Low Rate

scholarly journals Signal, bias, and the role of transcriptome assembly quality in phylogenomic inference

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Jennifer L. Spillane ◽  
Troy M. LaPolice ◽  
Matthew D. MacManes ◽  
David C. Plachetzki
Keyword(s):  
Evolutionary History ◽  
Transcriptome Assembly ◽  
Phylogenetic Signal ◽  
Poor Quality ◽  
Compositional Bias ◽  
Assembly Quality ◽  
High Quality ◽  
Downstream Effects ◽  
Phylogenomic Analyses

Abstract Background Phylogenomic approaches have great power to reconstruct evolutionary histories, however they rely on multi-step processes in which each stage has the potential to affect the accuracy of the final result. Many studies have empirically tested and established methodology for resolving robust phylogenies, including selecting appropriate evolutionary models, identifying orthologs, or isolating partitions with strong phylogenetic signal. However, few have investigated errors that may be initiated at earlier stages of the analysis. Biases introduced during the generation of the phylogenomic dataset itself could produce downstream effects on analyses of evolutionary history. Transcriptomes are widely used in phylogenomics studies, though there is little understanding of how a poor-quality assembly of these datasets could impact the accuracy of phylogenomic hypotheses. Here we examined how transcriptome assembly quality affects phylogenomic inferences by creating independent datasets from the same input data representing high-quality and low-quality transcriptome assembly outcomes. Results By studying the performance of phylogenomic datasets derived from alternative high- and low-quality assembly inputs in a controlled experiment, we show that high-quality transcriptomes produce richer phylogenomic datasets with a greater number of unique partitions than low-quality assemblies. High-quality assemblies also give rise to partitions that have lower alignment ambiguity and less compositional bias. In addition, high-quality partitions hold stronger phylogenetic signal than their low-quality transcriptome assembly counterparts in both concatenation- and coalescent-based analyses. Conclusions Our findings demonstrate the importance of transcriptome assembly quality in phylogenomic analyses and suggest that a portion of the uncertainty observed in such studies could be alleviated at the assembly stage.

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