Evidence map›Paper›PMID 33299096›Full record

ArticleScientific reports2020

Computational insights into RNAi-based therapeutics for foot and mouth disease of Bos taurus.

Tanmaya Kumar Sahu, Anoop Kishor Singh Gurjar, Prabina Kumar Meher, Cini Varghese, Sudeep Marwaha, Govind Pratap Rao, Anil Rai, Neha Guleria, Suresh H Basagoudanavar, Aniket Sanyal and 1 more

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact, top 80% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed, 4 citations in OpenAlex.

  1. Review
  2. Review
  3. Article
  4. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors at 3 institutions in 1 country.

Tanmaya Kumar SahuICAR-Indian Agricultural Statistics Research Institute, New Delhi, India.ORCID 0000-0003-0799-0660
Anoop Kishor Singh GurjarICAR-Indian Agricultural Statistics Research Institute, New Delhi, India.
Prabina Kumar MeherICAR-Indian Agricultural Statistics Research Institute, New Delhi, India.
Cini VargheseICAR-Indian Agricultural Statistics Research Institute, New Delhi, India.
Sudeep MarwahaICAR-Indian Agricultural Statistics Research Institute, New Delhi, India.
Govind Pratap RaoICAR-Indian Agricultural Research Institute, New Delhi, India.
Anil RaiICAR-Indian Agricultural Statistics Research Institute, New Delhi, India.
Neha GuleriaICAR-Indian Veterinary Research Institute, Bengaluru, India.
Suresh H BasagoudanavarICAR-Indian Veterinary Research Institute, Bengaluru, India.ORCID 0000-0001-7714-3120
Aniket SanyalICAR-Indian Veterinary Research Institute, Bengaluru, India.
Atmakuri Ramakrishna RaoICAR-Indian Agricultural Statistics Research Institute, New Delhi, India. rao.cshl.work@gmail.com.ORCID 0000-0002-3914-6248
Indian Agricultural Statistics Research Institute · INIndian Veterinary Research Institute · INIndian Agricultural Research Institute · IN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Foot-and-mouth disease (FMD) endangers a large number of livestock populations across the globe being a highly contagious viral infection in wild and domestic cloven-hoofed animals. It adversely affects the socioeconomic status of millions of households. Vaccination has been used to protect animals against FMD virus (FMDV) to some extent but the effectiveness of available vaccines has been decreased due to high genetic variability in the FMDV genome. Another key aspect that the current vaccines are not favored is they do not provide the ability to differentiate between infected and vaccinated animals. Thus, RNA interference (RNAi) being a potential strategy to control virus replication, has opened up a new avenue for controlling the viral transmission. Hence, an attempt has been made here to establish the role of RNAi in therapeutic developments for FMD by computationally identifying (i) microRNA (miRNA) targets in FMDV using target prediction algorithms, (ii) targetable genomic regions in FMDV based on their dissimilarity with the host genome and, (iii) plausible anti-FMDV miRNA-like simulated nucleotide sequences (SNSs). The results revealed 12 mature host miRNAs that have 284 targets in 98 distinct FMDV genomic sequences. Wet-lab validation for anti-FMDV properties of 8 host miRNAs was carried out and all were observed to confer variable magnitude of antiviral effect. In addition, 14 miRBase miRNAs were found with better target accessibility in FMDV than that of Bos taurus. Further, 8 putative targetable regions having sense strand properties of siRNAs were identified on FMDV genes that are highly dissimilar with the host genome. A total of 16 SNSs having > 90% identity with mature miRNAs were also identified that have targets in FMDV genes. The information generated from this study is populated at http://bioinformatics.iasri.res.in/fmdisc/ to cater the needs of biologists, veterinarians and animal scientists working on FMD.

Indexed as

RNAi TherapeuticsAlgorithmsAnimalsCattleCattle DiseasesComputational BiologyFoot-and-Mouth DiseaseFoot-and-Mouth Disease Virus

Identifiers

PMID33299096
PMCPMC7725835
OpenAlexW3112005695

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.