scholarly journals Chromosome-scale assembly and whole-genome sequencing of 266 giant panda roundworms provide insights into their evolution, adaptation and potential drug targets

2021 ◽  
Author(s):  
Lei Han ◽  
Tianming Lan ◽  
Desheng Li ◽  
Haimeng Li ◽  
Linhua Deng ◽  
...  
Keyword(s):  
Disease Transmission ◽  
Population Genetic ◽  
Drug Targets ◽  
Giant Panda ◽  
Chitin Synthesis ◽  
Population Genetic Analysis ◽  
Adaptation Mechanism ◽  
Living Fossil ◽  
A Genome ◽  
The Impact

Helminth diseases have long been a threat to the health of humans and animals. Roundworms are important organisms for studying parasitic mechanisms, disease transmission and prevention. The study of parasites in the living fossil giant panda is of great significance for understanding the adaptation mechanism of roundworms to the host. Here, we report a high-quality chromosome-scale genome of Baylisascaris schroederi with a genome size of 262 Mb and 19,291 predicted protein-coding genes. We found a significant expansion of genes related to epidermal chitin synthesis and environmental information processing in roundworms genome. Furthermore, we demonstrated unique genes involved in essential amino acid metabolism in the B. schroederi genome, inferred to be essential for the adaptation to the giant panda-specific diet. In addition, under different deworming pressures, we found that four resistance-related genes (glc-1, nrf-6, bre-4 and ced-7) were under strong positive selection in captive population. Finally, 23 known drug targets and 47 potential target proteins were identified. The genome provides a unique reference for inferring the early evolution of roundworms and the mechanisms underlying adaptive. Population genetic analysis and drug prediction provide insights for revealing the impact of deworming history on population genetic structure and prevention.

scholarly journals Chromosome-scale assembly and whole-genome sequencing of 266 giant panda roundworms provide insights into their evolution, adaptation and potential drug targets

2021 ◽  
Author(s):  
Lei Han ◽  
Tianming Lan ◽  
Desheng Li ◽  
Haimeng Li ◽  
Linhua Deng ◽  
...  
Keyword(s):  
Disease Transmission ◽  
Population Genetic ◽  
Drug Targets ◽  
Giant Panda ◽  
Host Population ◽  
Potential Drug ◽  
Chitin Synthesis ◽  
Population Genetic Analysis ◽  
A Genome ◽  
The Impact

Helminth diseases have long been a threat to the health of humans and animals. Roundworms are important organisms for studying parasitic mechanisms, disease transmission and prevention. The study of parasites in the giant panda is of importance for understanding how roundworms adapt to the host. Here, we report a high-quality chromosome-scale genome of Baylisascaris schroederi with a genome size of 253.60 Mb and 19,262 predicted protein-coding genes. We found that gene families related to epidermal chitin synthesis and environmental information processes in the roundworm genome have expanded significantly. Furthermore, we demonstrated unique genes involved in essential amino acid metabolism in the B. schroederi genome, inferred to be essential for the adaptation to the giant panda-specific diet. In addition, under different deworming pressures, we found that four resistance-related genes (glc-1, nrf-6, bre-4 and ced-7) were under strong positive selection in a captive population. Finally, 23 known drug targets and 47 potential drug target proteins (essential homologues linked to lethal phenotypes) were identified. The genome provides a unique reference for inferring the early evolution of roundworms and their adaptation to the host. Population genetic analysis and drug sensitivity prediction provide insights revealing the impact of deworming history on population genetic structure of importance for disease prevention.

scholarly journals SINE jumping contributes to large-scale polymorphisms in the pig genomes

2021 ◽  
Author(s):  
Cai Chen ◽  
Enrico D'Alessandro ◽  
Eduard Murani ◽  
Yao Zheng ◽  
Domenico Giosa ◽  
...  
Keyword(s):  
Genetic Analysis ◽  
Population Genetic ◽  
Large Scale ◽  
Structural Variations ◽  
Population Genetic Analysis ◽  
Protein Coding ◽  
Pig Breeds ◽  
A Genome ◽  
Trait Locus ◽  
And Cluster Analysis

Abstract Background: Molecular markers based on retrotransposon insertion polymorphisms (RIPs) have been developed and are widely used in plants and animals. Short interspersed nuclear elements (SINEs) exert wide impacts on gene activity and even on phenotypes. However, SINE RIP profiles in livestock remain largely unknown, and not be revealed in pigs. Results: Our data revealed that SINEA1 displayed the most polymorphic insertions (22.5% intragenic and 26.5% intergenic), followed by SINEA2 (10.5% intragenic and 9% intergenic) and SINEA3 (12.5% intragenic and 5.0% intergenic). We developed a genome-wide SINE RIP mining protocol and obtained a large number of SINE RIPs (36,284), with over 80% accuracy and an even distribution in chromosomes (14.5/Mb), and 74.34% of SINE RIPs generated by SINEA1 element. Over 65% of pig SINE RIPs overlap with genes, with significant enrichment in the first and second introns of protein-coding and long non-coding RNA genes. Nearly half of the RIPs are common in these pig breeds. Sixteen SINE RIPs were applied for population genetic analysis in 23 pig breeds, the phylogeny tree and cluster analysis were generally consistent with the geographical distributions of native pig breeds in China. Conclusions: Our analysis revealed that SINEA1–3 elements, particularly SINEA1, are high polymorphic across different pig breeds, and generate large-scale structural variations in the pig genomes. And over 35, 000 SINE RIP markers were obtained. These data indicate that young SINE elements play important roles in creating new genetic variations and shaping the evolution of pig genome, and also provide strong evidences to support the great potential of SINE RIPs as genetic markers, which can be used for population genetic analysis and quantitative trait locus (QTL) mapping in pig.

scholarly journals Swayne's hartebeest in Ethiopia: population estimate, genetic variability and competition with livestock

Oryx ◽  
2021 ◽  
pp. 1-9
Author(s):  
Misganaw Tamrat ◽  
Anagaw Atickem ◽  
Øystein Flagstad ◽  
Martha Fischer ◽  
Christian Roos ◽  
...  
Keyword(s):  
Protected Areas ◽  
Disease Transmission ◽  
Population Genetic ◽  
National Park ◽  
Resource Competition ◽  
Population Decline ◽  
Iucn Red List ◽  
Ethiopian Rift ◽  
Population Genetic Analysis ◽  
D Loop

Abstract Swayne's hartebeest Alcelaphus buselaphus swaynei was once widely distributed in the Horn of Africa. By the early 20th century, however, it was extirpated across most of its range and is now limited to two relict populations in the Ethiopian Rift Valley and categorized as Endangered on the IUCN Red List. In this study, we estimated the size and genetic diversity of these two remaining populations, with a particular focus on competition with livestock. We used a total block count method for both Swayne's hartebeest and livestock population counts, and faecal samples for a population genetic analysis. We estimated the total population of Swayne's hartebeest to be 1,528, with 518 individuals in Senkele Swayne's Hartebeest Sanctuary and 1,010 individuals in Maze National Park. Livestock densities were 212 and 153 times those of Swayne's hartebeest in Senkele Swayne's Hartebeest Sanctuary and Maze National Park, respectively. Among 73 mitochondrial D-loop sequences (34 from Senkele Swayne's Hartebeest Sanctuary and 39 from Maze National Park), we found 22 haplotypes (Senkele 12, Maze 16, shared 6). Population genetic parameters suggest only weak sub-structuring between the two populations (FST = 0.164). Despite the positive population trends in both protected areas, the spatial overlap with livestock may lead to future population decline as a result of resource competition and disease transmission. We therefore recommend further translocation to other protected areas within the species’ former range.

scholarly journals SINE jumping contributes to large-scale polymorphisms in the pig genomes

Mobile DNA ◽  
2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Cai Chen ◽  
Enrico D’Alessandro ◽  
Eduard Murani ◽  
Yao Zheng ◽  
Domenico Giosa ◽  
...  
Keyword(s):  
Genetic Analysis ◽  
Population Genetic ◽  
Large Scale ◽  
Structural Variations ◽  
Population Genetic Analysis ◽  
Protein Coding ◽  
Pig Breeds ◽  
A Genome ◽  
Trait Locus ◽  
And Cluster Analysis

Abstract Background Molecular markers based on retrotransposon insertion polymorphisms (RIPs) have been developed and are widely used in plants and animals. Short interspersed nuclear elements (SINEs) exert wide impacts on gene activity and even on phenotypes. However, SINE RIP profiles in livestock remain largely unknown, and not be revealed in pigs. Results Our data revealed that SINEA1 displayed the most polymorphic insertions (22.5 % intragenic and 26.5 % intergenic), followed by SINEA2 (10.5 % intragenic and 9 % intergenic) and SINEA3 (12.5 % intragenic and 5.0 % intergenic). We developed a genome-wide SINE RIP mining protocol and obtained a large number of SINE RIPs (36,284), with over 80 % accuracy and an even distribution in chromosomes (14.5/Mb), and 74.34 % of SINE RIPs generated by SINEA1 element. Over 65 % of pig SINE RIPs overlap with genes, most of them (> 95 %) are in introns. Overall, about one forth (23.09 %) of the total genes contain SINE RIPs. Significant biases of SINE RIPs in the transcripts of protein coding genes were observed. Nearly half of the RIPs are common in these pig breeds. Sixteen SINE RIPs were applied for population genetic analysis in 23 pig breeds, the phylogeny tree and cluster analysis were generally consistent with the geographical distributions of native pig breeds in China. Conclusions Our analysis revealed that SINEA1–3 elements, particularly SINEA1, are high polymorphic across different pig breeds, and generate large-scale structural variations in the pig genomes. And over 35,000 SINE RIP markers were obtained. These data indicate that young SINE elements play important roles in creating new genetic variations and shaping the evolution of pig genome, and also provide strong evidences to support the great potential of SINE RIPs as genetic markers, which can be used for population genetic analysis and quantitative trait locus (QTL) mapping in pig.

scholarly journals Population genomics of Mediterranean oat (A. sativa) reveals high genetic diversity and three loci for heading date

2021 ◽  
Author(s):  
F. J. Canales ◽  
G. Montilla-Bascón ◽  
W. A. Bekele ◽  
C. J. Howarth ◽  
T. Langdon ◽  
...  
Keyword(s):  
Genetic Diversity ◽  
Genetic Analysis ◽  
Population Genetic ◽  
Large Scale ◽  
Population Genomics ◽  
Heading Date ◽  
Population Genetic Analysis ◽  
High Genetic Diversity ◽  
A Genome ◽  
Interactive Map

Key messageGenomic analysis of Mediterranean oats reveals high genetic diversity and three loci for adaptation to this environment. This information together with phenotyping and passport data, gathered in an interactive map, will be a vital resource for oat genetic improvement.AbstractDuring the twentieth century, oat landraces have increasingly been replaced by modern cultivars, resulting in loss of genetic diversity. However, landraces have considerable potential to improve disease and abiotic stress tolerance and may outperform cultivars under low input systems. In this work, we assembled a panel of 669 oat landraces from Mediterranean rim and 40 cultivated oat varieties and performed the first large-scale population genetic analysis of both red and white oat types of Mediterranean origin. We created a public database associated with an interactive map to visualize information for each accession. The oat collection was genotyped with 17,288 single-nucleotide polymorphism (SNP) loci to evaluate population structure and linkage disequilibrium (LD); to perform a genome-wide association study (GWAs) for heading date, a key character closely correlated with performance in this drought-prone area. Population genetic analysis using both structure and PCA distinguished two main groups composed of the red and white oats, respectively. The white oat group was further divided into two subgroups. LD decay was slower within white lines in linkage groups Mrg01, 02, 04, 12, 13, 15, 23, 33, whereas it was slower within red lines in Mrg03, 05, 06, 11, 21, 24, and 28. Association analysis showed several significant markers associated with heading date on linkage group Mrg13 in white oats and on Mrg01 and Mrg08 in red oats.

Recent Advances of In-Silico Modeling of Potent Antagonists for the Adenosine Receptors

2019 ◽  
Vol 25 (7) ◽  
pp. 750-773 ◽  
Author(s):  
Pabitra Narayan Samanta ◽  
Supratik Kar ◽  
Jerzy Leszczynski
Keyword(s):  
Drug Targets ◽  
Biological Activities ◽  
Scoring Function ◽  
Md Simulations ◽  
Energy Calculation ◽  
Binding Modes ◽  
Macromolecular Systems ◽  
In Silico Modeling ◽  
Mathematical Algorithms ◽  
The Impact

The rapid advancement of computer architectures and development of mathematical algorithms offer a unique opportunity to leverage the simulation of macromolecular systems at physiologically relevant timescales. Herein, we discuss the impact of diverse structure-based and ligand-based molecular modeling techniques in designing potent and selective antagonists against each adenosine receptor (AR) subtype that constitutes multitude of drug targets. The efficiency and robustness of high-throughput empirical scoring function-based approaches for hit discovery and lead optimization in the AR family are assessed with the help of illustrative examples that have led to nanomolar to sub-micromolar inhibition activities. Recent progress in computer-aided drug discovery through homology modeling, quantitative structure-activity relation, pharmacophore models, and molecular docking coupled with more accurate free energy calculation methods are reported and critically analyzed within the framework of structure-based virtual screening of AR antagonists. Later, the potency and applicability of integrated molecular dynamics (MD) methods are addressed in the context of diligent inspection of intricated AR-antagonist binding processes. MD simulations are exposed to be competent for studying the role of the membrane as well as the receptor flexibility toward the precise evaluation of the biological activities of antagonistbound AR complexes such as ligand binding modes, inhibition affinity, and associated thermodynamic and kinetic parameters.

scholarly journals Estimating asymptomatic, undetected and total cases for the COVID-19 outbreak in Wuhan: a mathematical modeling study

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Xi Huo ◽  
Jing Chen ◽  
Shigui Ruan
Keyword(s):  
Disease Transmission ◽  
Large Scale ◽  
Transmission Rate ◽  
Control Strategies ◽  
Herd Immunity ◽  
Antibody Prevalence ◽  
Screening Process ◽  
Vaccination Programs ◽  
Prevalence Level ◽  
The Impact

Abstract Background The COVID-19 outbreak in Wuhan started in December 2019 and was under control by the end of March 2020 with a total of 50,006 confirmed cases by the implementation of a series of nonpharmaceutical interventions (NPIs) including unprecedented lockdown of the city. This study analyzes the complete outbreak data from Wuhan, assesses the impact of these public health interventions, and estimates the asymptomatic, undetected and total cases for the COVID-19 outbreak in Wuhan. Methods By taking different stages of the outbreak into account, we developed a time-dependent compartmental model to describe the dynamics of disease transmission and case detection and reporting. Model coefficients were parameterized by using the reported cases and following key events and escalated control strategies. Then the model was used to calibrate the complete outbreak data by using the Monte Carlo Markov Chain (MCMC) method. Finally we used the model to estimate asymptomatic and undetected cases and approximate the overall antibody prevalence level. Results We found that the transmission rate between Jan 24 and Feb 1, 2020, was twice as large as that before the lockdown on Jan 23 and 67.6% (95% CI [0.584,0.759]) of detectable infections occurred during this period. Based on the reported estimates that around 20% of infections were asymptomatic and their transmission ability was about 70% of symptomatic ones, we estimated that there were about 14,448 asymptomatic and undetected cases (95% CI [12,364,23,254]), which yields an estimate of a total of 64,454 infected cases (95% CI [62,370,73,260]), and the overall antibody prevalence level in the population of Wuhan was 0.745% (95% CI [0.693%,0.814%]) by March 31, 2020. Conclusions We conclude that the control of the COVID-19 outbreak in Wuhan was achieved via the enforcement of a combination of multiple NPIs: the lockdown on Jan 23, the stay-at-home order on Feb 2, the massive isolation of all symptomatic individuals via newly constructed special shelter hospitals on Feb 6, and the large scale screening process on Feb 18. Our results indicate that the population in Wuhan is far away from establishing herd immunity and provide insights for other affected countries and regions in designing control strategies and planing vaccination programs.

Systematic benchmark of ancient DNA read mapping

2021 ◽  
Author(s):  
Adrien Oliva ◽  
Raymond Tobler ◽  
Alan Cooper ◽  
Bastien Llamas ◽  
Yassine Souilmi
Keyword(s):  
Ancient Dna ◽  
Dna Sequences ◽  
Population Genetic ◽  
Reference Genome ◽  
Population Data ◽  
Human Populations ◽  
Current Standard ◽  
Read Mapping ◽  
Reference Bias ◽  
The Impact

Abstract The current standard practice for assembling individual genomes involves mapping millions of short DNA sequences (also known as DNA ‘reads’) against a pre-constructed reference genome. Mapping vast amounts of short reads in a timely manner is a computationally challenging task that inevitably produces artefacts, including biases against alleles not found in the reference genome. This reference bias and other mapping artefacts are expected to be exacerbated in ancient DNA (aDNA) studies, which rely on the analysis of low quantities of damaged and very short DNA fragments (~30–80 bp). Nevertheless, the current gold-standard mapping strategies for aDNA studies have effectively remained unchanged for nearly a decade, during which time new software has emerged. In this study, we used simulated aDNA reads from three different human populations to benchmark the performance of 30 distinct mapping strategies implemented across four different read mapping software—BWA-aln, BWA-mem, NovoAlign and Bowtie2—and quantified the impact of reference bias in downstream population genetic analyses. We show that specific NovoAlign, BWA-aln and BWA-mem parameterizations achieve high mapping precision with low levels of reference bias, particularly after filtering out reads with low mapping qualities. However, unbiased NovoAlign results required the use of an IUPAC reference genome. While relevant only to aDNA projects where reference population data are available, the benefit of using an IUPAC reference demonstrates the value of incorporating population genetic information into the aDNA mapping process, echoing recent results based on graph genome representations.

scholarly journals Evolution of disease transmission during the COVID-19 pandemic: patterns and determinants

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Jie Zhu ◽  
Blanca Gallego
Keyword(s):  
Public Health ◽  
Disease Transmission ◽  
Clustering Algorithm ◽  
Health Interventions ◽  
Transmission Model ◽  
Model Parameters ◽  
Public Health Interventions ◽  
Forecasting Accuracy ◽  
Time Lagged ◽  
The Impact

AbstractEpidemic models are being used by governments to inform public health strategies to reduce the spread of SARS-CoV-2. They simulate potential scenarios by manipulating model parameters that control processes of disease transmission and recovery. However, the validity of these parameters is challenged by the uncertainty of the impact of public health interventions on disease transmission, and the forecasting accuracy of these models is rarely investigated during an outbreak. We fitted a stochastic transmission model on reported cases, recoveries and deaths associated with SARS-CoV-2 infection across 101 countries. The dynamics of disease transmission was represented in terms of the daily effective reproduction number ($$R_t$$ R t ). The relationship between public health interventions and $$R_t$$ R t was explored, firstly using a hierarchical clustering algorithm on initial $$R_t$$ R t patterns, and secondly computing the time-lagged cross correlation among the daily number of policies implemented, $$R_t$$ R t , and daily incidence counts in subsequent months. The impact of updating $$R_t$$ R t every time a prediction is made on the forecasting accuracy of the model was investigated. We identified 5 groups of countries with distinct transmission patterns during the first 6 months of the pandemic. Early adoption of social distancing measures and a shorter gap between interventions were associated with a reduction on the duration of outbreaks. The lagged correlation analysis revealed that increased policy volume was associated with lower future $$R_t$$ R t (75 days lag), while a lower $$R_t$$ R t was associated with lower future policy volume (102 days lag). Lastly, the outbreak prediction accuracy of the model using dynamically updated $$R_t$$ R t produced an average AUROC of 0.72 (0.708, 0.723) compared to 0.56 (0.555, 0.568) when $$R_t$$ R t was kept constant. Monitoring the evolution of $$R_t$$ R t during an epidemic is an important complementary piece of information to reported daily counts, recoveries and deaths, since it provides an early signal of the efficacy of containment measures. Using updated $$R_t$$ R t values produces significantly better predictions of future outbreaks. Our results found variation in the effect of early public health interventions on the evolution of $$R_t$$ R t over time and across countries, which could not be explained solely by the timing and number of the adopted interventions.

scholarly journals Impact of COVID-19 on workload burden of a complex radiotherapy facility

2021 ◽  
Vol 126 (5) ◽  
pp. 717-721
Author(s):  
Giulio Francolini ◽  
Isacco Desideri ◽  
Giulia Stocchi ◽  
Lucia Pia Ciccone ◽  
Viola Salvestrini ◽  
...  
Keyword(s):  
Disease Transmission ◽  
Daily Activity ◽  
Preventive Measures ◽  
Health Workers ◽  
Treatment Delivery ◽  
Actual Time ◽  
Italian Government ◽  
Significant Difference ◽  
The Impact ◽  
Observation Period

Abstract Background and purpose COVID-19 constitutes a worldwide threat, prompting Italian Government to implement specific measures on March 8, 2020, to protect patients and health workers from disease transmission. The impact of preventive measures on daily activity of a radiotherapy facility may hamper the ability to fulfill normal workload burden. Thus, we assessed the number of delivered treatments in a specific observation period after the adoption of preventive measures (since March 11 to April 24, 2020) and compared it with the corresponding period of the year 2019. Materials and methods Overall number of delivered fractions was related to actual time of platform daily activity and reported as a ratio between number of delivered fractions and activity hours (Fr/Hrs). Fr/Hrs were calculated and compared for two different periods of time, March 11–April 24, 2019 (Fr/Hrs1), and March 11–April 24, 2020 (Fr/Hrs2). Results Fr/Hrs1 and Fr/Hrs2 were 2.66 and 2.54 for year 2019 and 2020, respectively, for a Fr/Hrsratio of 1.07 (95% CI 1.03–1.12, p = 0.0005). Fr/Hrs1 was significantly higher than Fr/Hrs2 for SliR and PreciseR, with Fr/Hrsratio of 1.92 (95% CI 1.66–2.23, p < 0.0001) and 1.11 (95% CI 1.03–1.2, p = 0.003), respectively. No significant difference was reported for SynergyR and CyberknifeR with Fr/Hrsratio of 0.99 (95% CI 0.91–1.08, p = 0.8) and 0.9 (95% CI 0.77–1.06, p = 0.2), respectively. Fr/Hrs1 was significantly lower than Fr/Hrs2 for TomotherapyR, with Fr/Hrsratio of 0.88 (95% CI 0.8–0.96, p = 0.007). Conclusion Preventive measures did not influence workload burden performed. Automation in treatment delivery seems to compensate effectively for health workers number reduction.

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