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> Genes & Molecular Sequences > Gene or Genome > Viral Genome

Viral Genome

Viral genomes refer to the complete set of genetic material, including DNA or RNA, that encode the structural and functional components of viruses.
These genomes play a crucial role in viral replication, host specificity, and pathogenicity.
Understanding the genetic makeup of viruses is essential for developing effective diagnostic tools, therapeutic interventions, and preventive measures against viral infections.
Researchers utilize advanced techniques, such as sequencing and bioinformatic analysis, to study viral genomes and unravel the complexities of viral biology.
This knowledge contributes to the advancement of virology, epidemiology, and public health efforts to combat emerging and re-emerging viral diseases.
Expereience the power of AI-driven research optimization with PubCompare.ai to enhance reproducibility and accuracy in viral genome studies.

Most cited protocols related to «Viral Genome»

1
Kraken 2 Database Enhancements
The CHT’s modest memory requirements, and the additional savings yielded by minimizer-based subsampling, allow more reference genomic data to be included in Kraken 2’s standard reference library. Whereas Kraken 1’s default database had data from archeal, bacterial, and viral genomes, Kraken 2’s default database additionally includes the GRCh38 assembly of the human genome [29 (link)] and the “UniVec_Core” subset of the UniVec database [30 ]. We include these in Kraken 2’s default database to allow for easier classification of human microbiome reads and more accurate classification of reads containing vector sequences.
Additionally, we have implemented masking of low-complexity sequences from reference sequences in Kraken 2, by using the “dustmasker” [31 (link)] (for nucleotide sequences) and “segmasker” [32 (link)] (for protein sequences) tools from NCBI. Using the tools’ default settings, nucleotide and protein sequences are checked for low-complexity regions, and those regions identified are masked and not processed further by the Kraken 2 database building process. In this manner, we seek to reduce false positives resulting from these low-complexity sequences, similar to the build process for Centrifuge [1 (link)].
Wood D.E., Lu J, & Langmead B. (2019). Improved metagenomic analysis with Kraken 2. Genome Biology, 20, 257.
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Publication 2019
Amino Acid Sequence Archaea Bacteria Base Sequence Cloning Vectors DNA Library Genome Genome, Human Human Microbiome Memory Nucleotides Viral Genome
2
Taxonomic Profiling of Human Microbiome
We classified the Human Microbiome Project data using a Kraken database made from complete RefSeq bacterial, archaeal and viral genomes, along with the GRCh37 human genome. We retrieved the sequences of three accessions (SRS019120, SRS014468 and SRS015055) from the NCBI Sequence Read Archive, and each accession had two runs submitted. All reads were trimmed to remove low quality bases and adapter sequences. Krona [24 (link)] was used to generate all taxonomic distribution plots.
Because the sequences were all paired reads, we joined the reads together by concatenating the mates with a sequence of ‘NNNNN’ between them. Kraken ignores k-mers with ambiguous nucleotides, so the k-mers that span these ‘N’ characters do not affect classification. This operation allowed Kraken to classify a pair of reads as a single unit rather than having to classify the mates separately.
Wood D.E, & Salzberg S.L. (2014). Kraken: ultrafast metagenomic sequence classification using exact alignments. Genome Biology, 15(3), R46.
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Publication 2014
Archaea Bacteria Character Genome, Human GPER protein, human Human Microbiome Nucleotides Viral Genome
3
ICTV Prokaryotic Virus Genomes Analysis
Genomes were taxonomically selected by querying the INSDC databases for all species names assigned to families of prokaryotic virus in the third version of the 2014 ICTV master species list (https://talk.ictvonline.org/files/master-species-lists/) (King et al., 2012 ), which contained a total of 548 species, 103 genera, 7 subfamilies and 18 families; we did not observe a new version in 2017 that contained more taxa. Using all available whole-genome sequences of prokaryotic viruses instead would enrich the dataset with informal taxon names that could hardly be compared with each other and to the formally accepted names in the ICTV master list. Genomes assigned to species sensu lato were also removed. The collected data were further restricted to complete genome sequences containing protein annotation. Duplicate genomes (due to distinct annotation versions) were detected using MD5 checksums calculated from their nucleotide sequences and only the version with most protein sequences kept. The reference dataset is listed in Supplementary File S1.
Meier-Kolthoff J.P, & Göker M. (2017). VICTOR: genome-based phylogeny and classification of prokaryotic viruses. Bioinformatics, 33(21), 3396-3404.
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Publication 2017
Amino Acid Sequence Base Sequence Genome Prokaryotic Cells Protein Annotation Speech Viral Genome Virus
4
RNA-Seq Analysis of Viral Infection Responses

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Publication 2020
Animals Biological Processes Cells Gene Expression Genes Genome Genome, Human GPER protein, human Infection Interferon Type I Love Middle East Respiratory Syndrome Coronavirus prisma RNA-Seq SARS-CoV-2 Severe acute respiratory syndrome-related coronavirus Viral Genome
5
Evaluating Viral Sequence Detection Tools
We first evaluated VirSorter results against the manually curated prophages from (Casjens, 2003 (link)). Each genome was processed with VirSorter, PhiSpy (Akhter, Aziz & Edwards, 2012 (link)), Phage_Finder (Fouts, 2006 (link)) and PHAST (Zhou et al., 2011 (link)). For each tool, a prophage was considered as “detected” when a prediction covered more than 75% of the known prophage. For a more detailed example case of prophage detection in a complete bacterial genome including both prophages and genomic islands, the same tools were applied to the manually annotated Pseudomonas aeruginosa LES B58 genome (Winstanley et al., 2009 (link)).
VirSorter was then compared with the same prophage detection tools on the set of simulated SAGs. In that case, a viral sequence was considered as detected if predicted as completely viral or as a prophage. All the additional detections were manually checked to verify if the region was indeed viral (originating from a prophage in one of the microbial genomes rather than from a viral genome) or a false positive. The same approach was used for the simulated microbial and viral metagenomes results.
For each set of predictions, two metrics are computed. First, the Recall value corresponds to the number of viral sequences correctly predicted divided by the total number of known viral sequences in the dataset, and reflects the ability of the tool to find every known viral sequence in the dataset. Second, the Precision value is computed as the total number of viral sequences correctly predicted divided by the total number of viral sequences predicted, and indicates how accurate the tool is in its identification of viral signal.
Roux S., Enault F., Hurwitz B.L, & Sullivan M.B. (2015). VirSorter: mining viral signal from microbial genomic data. PeerJ, 3, e985.
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Publication 2015
Bacteriophages DMBT1 protein, human Genome Genome, Bacterial Genome, Microbial Genomic Islands Mental Recall Metagenome Prophages Pseudomonas aeruginosa Viral Genome

Most recents protocols related to «Viral Genome»

1
In Vivo Albumin Gene Editing using Zinc Finger Nucleases
Not available on PMC !

Example 5

To deliver the albumin-specific ZFNs to the liver in vivo, the normal site of albumin production, we generated a hepatotropic adeno-associated virus vector, serotype 8 expressing the albumin-specific ZFNs from a liver-specific enhancer and promoter (Shen et al., ibid and Miao et al., ibid). Adult C57BL/6 mice were subjected to genome editing at the albumin gene as follows: adult mice were treated by i.v. (intravenous) injection with 1×1011 v.g. (viral genomes)/mouse of either ZFN pair 1 (SBS 30724 and SBS 30725), or ZFN pair 2 (SBS 30872 and SBS 30873) and sacrificed seven days later. The region of the albumin gene encompassing the target site for pair 1 was amplified by PCR for the Cel-I mismatch assay using the following 2 PCR primers:

Cel1 F1:
(SEQ ID NO: 69)
5′ CCTGCTCGACCATGCTATACT 3′
Cel1 R1:
(SEQ ID NO: 70)
5′ CAGGCCTTTGAAATGTTGTTC 3′

The region of the albumin gene encompassing the target site for pair 2 was amplified by PCR for the Cel-I assay using these PCR primers:

mAlb set4F4:
(SEQ ID NO: 71)
5′ AAGTGCAAAGCCTTTCAGGA 3′
mAlb set4R4:
(SEQ ID NO: 72)
5′ GTGTCCTTGTCAGCAGCCTT 3′

As shown in FIG. 4, the ZFNs induce indels in up to 17% of their target sites in vivo in this study.

The mouse albumin specific ZFNs SBS30724 and SBS30725 which target a sequence in intron 1 were also tested in a second study. Genes for expressing the ZFNs were introduced into an AAV2/8 vector as described previously (Li et al. (2011) Nature 475 (7355): 217). To facilitate AAV production in the baculovirus system, a baculovirus containing a chimeric serotype 8.2 capsid gene was used. Serotype 8.2 capsid differs from serotype 8 capsid in that the phopholipase A2 domain in capsid protein VP1 of AAV8 has been replaced by the comparable domain from the AAV2 capsid creating a chimeric capsid. Production of the ZFN containing virus particles was done either by preparation using a HEK293 system or a baculovirus system using standard methods in the art (See Li et al., ibid, see e.g., U.S. Pat. No. 6,723,551). The virus particles were then administered to normal male mice (n=6) using a single dose of 200 microliter of 1.0el 1 total vector genomes of either AAV2/8 or AAV2/8.2 encoding the mouse albumin-specific ZFN. 14 days post administration of rAAV vectors, mice were sacrificed, livers harvested and processed for DNA or total proteins using standard methods known in the art. Detection of AAV vector genome copies was performed by quantitative PCR. Briefly, qPCR primers were made specific to the bGHpA sequences within the AAV as follows:

Oligo200 (Forward)
(SEQ ID NO: 102)
5′-GTTGCCAGCCATCTGTTGTTT-3′
Oligo201 (Reverse)
(SEQ ID NO: 103)
5′-GACAGTGGGAGTGGCACCTT-3′
Oligo202 (Probe)
(SEQ ID NO: 104)
5′-CTCCCCCGTGCCTTCCTTGACC-3′

Cleavage activity of the ZFN was measured using a Cel-I assay performed using a LC-GX apparatus (Perkin Elmer), according to manufacturer's protocol. Expression of the ZFNs in vivo was measured using a FLAG-Tag system according to standard methods.

As shown in FIG. 5 (for each mouse in the study) the ZFNs were expressed, and cleave the target in the mouse liver gene. The % indels generated in each mouse sample is provided at the bottom of each lane. The type of vector and their contents are shown above the lanes. Mismatch repair following ZFN cleavage (indicated % indels) was detected at nearly 16% in some of the mice.

The mouse specific albumin ZFNs were also tested for in vivo activity when delivered via use of a variety of AAV serotypes including AAV2/5, AAV2/6, AAV2/8 and AAV2/8.2. In these AAV vectors, all the ZFN encoding sequence is flanked by the AAV2 ITRs, contain, and then encapsulated using capsid proteins from AAV5, 6, or 8, respectively. The 8.2 designation is the same as described above. The SBS30724 and SBS30725 ZFNs were cloned into the AAV as described previously (Li et al., ibid), and the viral particles were produced either using baculovirus or a HEK293 transient transfection purification as described above. Dosing was done in normal mice in a volume of 200 μL per mouse via tail injection, at doses from 5e10 to 1e12 vg per dose. Viral genomes per diploid mouse genome were analyzed at days 14, and are analyzed at days 30 and 60. In addition, ZFN directed cleavage of the albumin locus was analyzed by Cel-I assay as described previously at day 14 and is analyzed at days 30 and 60.

As shown in FIG. 6, cleavage was observed at a level of up to 21% indels. Also included in Figure are the samples from the previous study as a comparison (far right, “mini-mouse” study-D14 and a background band (“unspecific band”).

US11859190B2. Methods and compositions for regulation of transgene expression (2024-01-02). Sangamo Therapeutics, Inc. [US]. Inventors: Edward J. Rebar [US].
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Patent 2024
Adult Albumins Baculoviridae Biological Assay Capsid Proteins Chimera Cloning Vectors Cytokinesis Dependovirus Diploidy Genes Genome INDEL Mutation Introns Liver Males Mice, Inbred C57BL Mismatch Repair Mus Oligonucleotide Primers Protein Domain Proteins Tail Transfection Transients Viral Genome Virion
2
Confirming HSV1-TKmut Gene Expression in OTS-412
Not available on PMC !

Example 3

To confirm the introduction of the HSV1-TKmut gene expression in OTS-412, wild type vaccinia virus and OTS-412 were identified by restriction enzyme mapping. After respectively infecting the wild-type vaccinia virus and OTS-412 into human osteosarcoma cells, the viruses were isolated and viral genomic DNAs were extracted to obtain a negative control (Wild type-VV) and a positive control (OTS-412).

The obtained viral DNAs were digested with HindIII restriction enzyme (10 units/2.5 μg) and separated by size using a DNA electrophoresis apparatus (FIG. 5). As a result, when comparing the negative control group and the positive control group, four corresponding bands (arrows) and one mismatching band (dotted arrow) between 4 kb and 8 kb were identified. The mismatching band had a large gene size, which showed that the HSV1-TKmut gene and the firefly luciferase gene were inserted into the TK region of vaccinia virus. It was confirmed as a unique band pattern of OTS-412 different from that of the wild-type vaccinia virus. When the wild-type vaccinia virus and OTS-412 after several passages were compared with the control groups, the same band patterns as those of the respective control groups were observed, confirming that the HSV1-TKmut gene in OTS-412 had genetic stability.

US11857585B2. Oncolytic virus improved in safety and anticancer effect (2024-01-02). BIONOXX INC. [KR]. Inventors: Taeho Hwang [KR], Mong Cho [KR].
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Patent 2024
Cells Deoxyribonuclease HindIII DNA DNA, A-Form DNA, Viral Electrophoresis Gene Expression Genes Genome Homo sapiens Human Herpesvirus 1 Luciferases, Firefly Osteosarcoma Reproduction Vaccinia virus Viral Genome Virus
3
Predicting Genes and Comparing Viral Genomes
Not available on PMC !

Example 2

Genes were predicted using Gene Locator and Interpolated Markov ModelER (Glimmer)38. For each sequenced genome, protein sequences of known genes of the respective reference from GenBank were aligned with exonerate39 to the assembled genome sequence. The coordinates of the best hits were then used to build a Glimmer model which was subsequently used for prediction of location and orientation of genes in the sequenced genome.

Next, protein sequences were compared between virus genomes. The result of this analysis is given in FIG. 6. Shown are genome organisations for 28 sequenced human adenoviruses. Genes and their orientation are shown as gray-shaded shapes on both strands of the genome (solid line). All genomes show the canonical organization of the Mastadenovirus genus.

Shading of a gene reflects its maximum sequence divergence across all 28 viruses determined through an all-vs-all Blast analysis.

US11866724B2. Adenoviral vectors (2024-01-09). Gene Bridges GMBH [DE]. Inventors: Adrian Francis Stewart [DE], Jun Fu [DE], Anja Ehrhardt [DE], Eric Ehrke-Schulz [DE], Wenli Zhang [DE].
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Patent 2024
Adenoviruses Amino Acid Sequence Gene Annotation Genes Genome Genome, Human Mastadenovirus Viral Genome Virus
4
Structural Insights into SARS-CoV-2 Spike Protein and Antibody Interactions
Activity 3 starts with the instructor explaining
that, after the interaction of the spike protein with the entry receptor
ACE2, cleavage of the S1 domain is achieved by a protease. Proteolytic
cleavage is followed by conformational changes in S2, which allows
the fusion of the virus with the cellular membranes leading to the
cytoplasmatic release of the viral genome into the host cell.15 (link) Because the viral genome must access the cytoplasm,
every step of this process is important. Understanding the foundations
of these entry mechanisms allows researchers to design vaccines, antibodies,
small molecule inhibitors, and other potential therapeutics targeting
to prevent SARS-CoV-2 access into the host cell.
A brief outline
should be also provided to students about how the body fights illness
and how vaccines work. So, they must know that after bacteria or viruses
enter the human body they start to multiply, giving rise to infection
and causing disease. Immediately, the immune system is activated and
produces antibodies to fight off the infection, but this process requires
a few days, which is why we have symptoms such as fever, headache,
fatigue, or body aches. After the first infection, the immune system
will recognize the germ and will already know how to defend the body.
Vaccines contain attenuated or inactivated parts of a specific organism
which provoke a mimicked infection in the body helping the immune
system to create the specific antibodies. Of course, this simulated
infection can cause some symptoms which are common while the body
creates the new antibodies. Vaccines are the safest and most effective
way of protecting people from infections. Of course, they are not
perfect and a person can develop disease despite having been vaccinated,
although they will be at a much lower risk of becoming seriously ill.
Next, students load and overlay the structures with IDs: 7V2A,16 (link)7TB8,17 (link)7WPD,18 (link)7CZP,19 (link)7CZQ,19 (link) and 7JZL(20 (link)) (Figure S5).
All are complexes of the spike
protein with antibodies or inhibitors
bonded to the receptor binding domain (RBD). They must answer the
following two questions: (1) why do SARS-CoV-2 vaccines prevent
serious illness and save hundreds of thousands of lives? And
based on what they have learned: (2) what could be the influence
of virus variants on the efficacy of these antibodies, and why?At the end of these activities, most of the students made
the connection
between the observed structural features and the efficacy of vaccines,
concluding by themselves that antibodies or inhibitors act by blocking
the ACE2 binding of the spike protein and, as consequence, the viral
entry into the host cells.
During the sessions, the students
explained to the instructors
their respective answers to the questions and the instructors evaluated
them. In addition, a quick assessment of the student’s learning
can be done using a short questionnaire as such the one provided in
the SI. If desired, it can be carried
out with Kahoot or similar tools.
, & Maya C. (2023). Using PyMOL to Understand Why COVID-19 Vaccines Save Lives. Journal of Chemical Education, 100(3), 1351-1356.
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Publication 2023
Ache Angiotensin Converting Enzyme 2 Antibodies Antibodies, Viral Bacteria COVID-19 Vaccines Cytokinesis Cytoplasm Fatigue Fever Headache Human Body Infection inhibitors M protein, multiple myeloma Peptide Hydrolases Plasma Membrane Safety SARS-CoV-2 Student System, Immune Therapeutics Vaccines Viral Genome Virus
5
Chemogenetic Activation of PV+ Neurons in mPFC
Adeno-associated virus (AAV) designer receptors exclusively activated by designer drug (DREADD) vectors (Addgene) were stereotaxically infused in the ventromedial PFC (including the central part of the PrL and IL cortices) of male PV:Cre mice. Briefly, AAV2/hSyn-DIO-hm3D(Gq)-mCherry (“hM3DGq”) was injected bilaterally (0.5 μl/side, ∼1012 viral genomes/ml) into mPFC using the following coordinates: anteroposterior, +1.7 mm; mediolateral, ±0.2 mm; dorsoventral, −2.6 mm. AAV2/hSyn-DIO-mCherry was used as the control virus. Previous work demonstrated that chemogenetic activation of PV+ neurons from both PrL and IL regions increases anxiety-like behaviors in female mice (Page et al., 2019 (link)). To be able to compare our findings with this study, we opted to use a similar strategy. Mice remained undisturbed for at least 21 d after surgery to allow full expression of the DREADD virus in PV+ cells before the commencement of behavioral testing. All mice received a daily intraperitoneal injection of clozapine-N-oxide (CNO; 0.5 mg/kg) 30 min before daily handling or stressor throughout the UCMS period. After the completion of behavioral assays, viral injection sites were verified using a rabbit anti-DsRed antibody (1:1000; TaKaRa Bio) followed by an Alexa Fluor anti-rabbit 555 secondary antibody (1:500; Thermo Fisher Scientific) to target mCherry in prefrontal brain sections.
Woodward E., Rangel-Barajas C., Ringland A., Logrip M.L, & Coutellier L. (2023). Sex-Specific Timelines for Adaptations of Prefrontal Parvalbumin Neurons in Response to Stress and Changes in Anxiety- and Depressive-Like Behaviors. eNeuro, 10(3), ENEURO.0300-22.2023.
Full text: Click here
Publication 2023
Alexa Fluor 555 Antibodies, Anti-Idiotypic Anxiety Biological Assay Brain Cells Cloning Vectors clozapine N-oxide Cortex, Cerebral Designer Drugs Females Immunoglobulins Injections, Intraperitoneal Males Mus Neurons Operative Surgical Procedures Rabbits Receptors, Virus Vascular Access Ports Viral Genome Virus

Top products related to «Viral Genome»

1
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The QIAamp Viral RNA Mini Kit is a laboratory equipment designed for the extraction and purification of viral RNA from various sample types. It utilizes a silica-based membrane technology to efficiently capture and isolate viral RNA, which can then be used for downstream applications such as RT-PCR analysis.
2
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TRIzol reagent is a monophasic solution of phenol, guanidine isothiocyanate, and other proprietary components designed for the isolation of total RNA, DNA, and proteins from a variety of biological samples. The reagent maintains the integrity of the RNA while disrupting cells and dissolving cell components.
3
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4
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More about "Viral Genome"

Viral genomes are the complete set of genetic material, including DNA or RNA, that encode the structural and functional components of viruses.
These genomes play a pivotal role in viral replication, host specificity, and pathogenicity.
Understanding the genetic makeup of viruses is essential for developing effective diagnostic tools, therapeutic interventions, and preventive measures against viral infections.
Researchers utilize advanced techniques, such as sequencing and bioinformatic analysis, to study viral genomes and unravel the complexities of viral biology.
This knowledge contributes to the advancement of virology, epidemiology, and public health efforts to combat emerging and re-emerging viral diseases.
Key subtopics in viral genome research include viral RNA extraction using QIAamp Viral RNA Mini Kit, TRIzol reagent, and RNeasy Mini Kit, as well as viral DNA extraction using the DNeasy Blood and Tissue Kit and QIAamp DNA Mini Kit.
Reverse transcription and cDNA synthesis can be performed using SuperScript III Reverse Transcriptase, while viral transfection and expression can be facilitated by Lipofectamine 2000.
Advanced sequencing platforms, such as the MiSeq, play a crucial role in viral genome analysis, allowing researchers to uncover the genetic makeup and evolutionary patterns of viruses.
The use of fetal bovine serum (FBS) as a growth supplement is also common in viral culture and propagation studies.
By leveraging these tools and techniques, scientists can enhance the reproducability and accuracy of their viral genome research, ultimately contributing to a better understanding of viral biology and the development of effective interventions against viral diseases.