scholarly journals Genotyping Porcine Circovirus 3 (PCV-3) Nowadays: Does It Make Sense?

Viruses ◽  
2020 ◽  
Vol 12 (3) ◽  
pp. 265 ◽  
Author(s):  
Giovanni Franzo ◽  
Eric Delwart ◽  
Robert Fux ◽  
Ben Hause ◽  
Shuo Su ◽  
...  

The discovery of a globally distributed porcine circovirus (Porcine circovirus 3; PCV-3) has led to intense research activity and the production of a large amount of molecular data. Different research groups have proposed several, not always concordant, genotypes for this virus. While such categories could aid an easier interpretation of PCV-3 molecular epidemiology, any classification, to be useful in practical settings, must be univocal and of help in the understanding of underlying biological features and epidemiology. Based on these premises, the possibility of defining PCV-3 genotypes was evaluated on the broadest available dataset of PCV-3 complete genome (n = 357) and open reading frame 2 (ORF2, n = 653) sequences. Genetic distance and phylogenetic clustering were selected as the main objective criteria. Additional factors, including the number of within-cluster sequences, host and geographic clustering, concordance between different genomic regions, and analysis method were also taken in account to generate a classification that could be effectively applied in research and diagnostic settings. A maximum within-genotype genetic distance of 3% at the complete genome and 6% at the ORF2 levels, bootstrap support higher than 90%, and concordance between analysis methods allowed us to clearly define two clades which could be potentially defined as genotypes. Further subdivision was not suggested due to the absence of a meaningful association between PCV-3 and its biological/epidemiological features. Nevertheless, since one of the clades included two strains only, thus far we formally propose the definition of only one PCV-3 genotype (PCV-3a). The established criteria will allow us to automatically recognize other genotypes when more strain sequences are characterized.

2016 ◽  
Vol 4 (2) ◽  
Author(s):  
Qian Gong ◽  
Yi Hu ◽  
Yang Zhan ◽  
Dongliang Wang ◽  
Naidong Wang ◽  
...  

The complete genome of porcine circovirus type 2 (PCV2) strain YiY-3-2-H5 contains a cytidine insertion at position 962 in open reading frame 1. This insertion causes a reading frameshift of the rep gene, and thereafter a premature stop codon is present at the 3′ terminal end of this gene.


Author(s):  
Ana Paula Muterle Varela ◽  
Márcia Regina Loiko ◽  
Juliana da Silva Andrade ◽  
Caroline Tochetto ◽  
Samuel Paulo Cibulski ◽  
...  

Viruses ◽  
2019 ◽  
Vol 11 (3) ◽  
pp. 201 ◽  
Author(s):  
Giuliana Saraiva ◽  
Pedro Vidigal ◽  
Viviane Assao ◽  
Murilo Fajardo ◽  
Alerrandra Loreto ◽  
...  

Porcine circovirus 3 (PCV3) is an emerging virus that was first identified in the United States in 2016. Since its first detection, PCV3 has already been found in America, Asia, and Europe. Although PCV3 has already been described in Brazil, knowledge of its detection and sequence variation before 2016 is limited, as well as its distribution in the main swine producing regions of Brazil. In this study, 67 porcine clinical samples collected from nine states in Brazil between 2006 and 2007 were analyzed for PCV3 infection by PCR. Results showed that 47.8% of the samples were PCV3 positive, across all nine states. Of the PCV3-positive samples, 37.5% were also positive for PCV2. Interestingly, no clinical signs were associated with samples that were detected singularly with PCV3 infection. Moreover, the positive PCV3 rate in healthy pigs was higher (29.8%) than that found in unhealthy pigs (17.9%), suggesting that most pigs could live with PCV3 infection without any clinical sign in the analyzed samples. Nucleotide sequence analysis showed that PCV3 strains obtained in this study shared 94.44% to 99.83% sequence identity at the open reading frame 2 (ORF2) gene level with available strains from different countries. PCV3 Brazilian sequences collected in 2006 and 2007 shared 97.94% to 99.62% identity with the strains obtained in 2016. The results of neutrality and selective pressure tests indicated that the PCV3 Cap protein seems unable to tolerate high levels of variation on its sequence. Phylogenetic analysis grouped the Brazilian strains in PCV3a and PCV3b genotypes clusters, both including strains collected in America, Asia, and Europe. Taking the results together, multiple events of introduction of PCV3 may have occurred in Brazil, and Brazilian PCV3 strains may show genetic stability over the past 10 years.


2018 ◽  
Vol 6 (7) ◽  
Author(s):  
Can Liu ◽  
Shasha Chen ◽  
Fanwei Meng ◽  
Rui Chen ◽  
Zhigang Zhang ◽  
...  

ABSTRACT Two porcine circovirus 3 (PCV3) strains, named NWHEB21 and NWHUN2, were identified in heart and brain tissues of aborted piglets. Their complete genome sequences were sequenced and analyzed to further characterize PCV3 in China and worldwide.


2018 ◽  
Vol 1 (1) ◽  
Author(s):  
Nguyen Van Giap ◽  
Chung Hee Chun ◽  
Huynh Thi My Le ◽  
Cao Thi Bich Phuong ◽  
Vu Thi Ngoc ◽  
...  

Drones ◽  
2021 ◽  
Vol 5 (2) ◽  
pp. 52
Author(s):  
Thomas Lee ◽  
Susan Mckeever ◽  
Jane Courtney

With the rise of Deep Learning approaches in computer vision applications, significant strides have been made towards vehicular autonomy. Research activity in autonomous drone navigation has increased rapidly in the past five years, and drones are moving fast towards the ultimate goal of near-complete autonomy. However, while much work in the area focuses on specific tasks in drone navigation, the contribution to the overall goal of autonomy is often not assessed, and a comprehensive overview is needed. In this work, a taxonomy of drone navigation autonomy is established by mapping the definitions of vehicular autonomy levels, as defined by the Society of Automotive Engineers, to specific drone tasks in order to create a clear definition of autonomy when applied to drones. A top–down examination of research work in the area is conducted, focusing on drone navigation tasks, in order to understand the extent of research activity in each area. Autonomy levels are cross-checked against the drone navigation tasks addressed in each work to provide a framework for understanding the trajectory of current research. This work serves as a guide to research in drone autonomy with a particular focus on Deep Learning-based solutions, indicating key works and areas of opportunity for development of this area in the future.


2021 ◽  
Vol 59 ◽  
pp. 101763
Author(s):  
Wuyin Zhang ◽  
Liang Xu ◽  
Qi Liu ◽  
Yingli Cao ◽  
Kankan Yang ◽  
...  

BMC Genomics ◽  
2014 ◽  
Vol 15 (1) ◽  
pp. 408 ◽  
Author(s):  
Cristina Rodriguez-Fontenla ◽  
Manuel Calaza ◽  
Antonio Gonzalez

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