Evidence map›Paper›PMID 22276113›Full record

ArticlePloS one2012

RNA-seq based transcriptional map of bovine respiratory disease pathogen "Histophilus somni 2336".

Ranjit Kumar, Mark L Lawrence, James Watt, Amanda M Cooksey, Shane C Burgess, Bindu Nanduri

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed
4.3field-weighted citation impact, top 5% 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

16 citing papers in PubMed, 36 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Single nucleotide polymorphisms in the bovine Histophilus somni genome; a comparison of new and old isolates.Canadian journal of veterinary research = Revue canadienne de recherche veterinaire · 2015
    Article
  8. Article
  9. Review
  10. Article
  11. Article
  12. Computational small RNA prediction in bacteria.Bioinformatics and biology insights · 2013
    Article
  13. Article
  14. Article
  15. Predicting sRNAs and their targets in bacteria.Genomics, proteomics & bioinformatics · 2012
    Review
  16. 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

6 authors at 4 institutions in 1 country.

Ranjit KumarCollege of Veterinary Medicine, Mississippi State University, Mississippi State, Mississippi, United States of America.
Mark L Lawrence
James Watt
Amanda M Cooksey
Shane C Burgess
Bindu Nanduri
Mississippi State University · USEagle Engineering (United States) · USUniversity of Alabama at Birmingham · USUniversity of Arizona · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Genome structural annotation, i.e., identification and demarcation of the boundaries for all the functional elements in a genome (e.g., genes, non-coding RNAs, proteins and regulatory elements), is a prerequisite for systems level analysis. Current genome annotation programs do not identify all of the functional elements of the genome, especially small non-coding RNAs (sRNAs). Whole genome transcriptome analysis is a complementary method to identify "novel" genes, small RNAs, regulatory regions, and operon structures, thus improving the structural annotation in bacteria. In particular, the identification of non-coding RNAs has revealed their widespread occurrence and functional importance in gene regulation, stress and virulence. However, very little is known about non-coding transcripts in Histophilus somni, one of the causative agents of Bovine Respiratory Disease (BRD) as well as bovine infertility, abortion, septicemia, arthritis, myocarditis, and thrombotic meningoencephalitis. In this study, we report a single nucleotide resolution transcriptome map of H. somni strain 2336 using RNA-Seq method.The RNA-Seq based transcriptome map identified 94 sRNAs in the H. somni genome of which 82 sRNAs were never predicted or reported in earlier studies. We also identified 38 novel potential protein coding open reading frames that were absent in the current genome annotation. The transcriptome map allowed the identification of 278 operon (total 730 genes) structures in the genome. When compared with the genome sequence of a non-virulent strain 129Pt, a disproportionate number of sRNAs (∼30%) were located in genomic region unique to strain 2336 (∼18% of the total genome). This observation suggests that a number of the newly identified sRNAs in strain 2336 may be involved in strain-specific adaptations.

Indexed as

AnimalsBase SequenceCattleCattle DiseasesGene Expression ProfilingHaemophilus somnusRespiratory Tract DiseasesRNA, BacterialRNA, Small UntranslatedRNA, BacterialRNA, Small Untranslated

Identifiers

PMID22276113
PMCPMC3262788
OpenAlexW2152844021

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.