Evidence map›Paper›PMID 23046475›Full record

ArticleBMC bioinformatics2012

Transcriptome profile of a bovine respiratory disease pathogen: Mannheimia haemolytica PHL213.

Joseph S Reddy, Ranjit Kumar, James M Watt, Mark L Lawrence, Shane C Burgess, Bindu Nanduri

Open access · goldAbstract read
In one paragraph

Article in BMC bioinformatics, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
1.1field-weighted citation impact, top 24% 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

10 citing papers in PubMed, 14 citations in OpenAlex.

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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.

Joseph S ReddyCollege of Veterinary Medicine, Mississippi State University, Mississippi State, MS 39762, USA.
Ranjit Kumar
James M Watt
Mark L Lawrence
Shane C Burgess
Bindu Nanduri
Mississippi State University · USEagle Engineering (United States) · USUniversity of Alabama at Birmingham · USUniversity of Arizona · US

Funding

Training and Mentoring Core P20GM103476 · NIGMS · UNIVERSITY OF SOUTHERN MISSISSIPPI · PI MICHAEL R GARRETT · 2012 to 2026
$60.2M
TOUGALOO PROTEOMICSP20RR016476 · NCRR · UNIVERSITY OF SOUTHERN MISSISSIPPI · PI KRAMER, WOLFGANG · 2001 to 2011
$30.4M
NCRR NIH HHS 5P20RR016476-11NIGMS NIH HHS 8 P20 GM103476-11
6 · The paper itself

Abstract

backgroundComputational methods for structural gene annotation have propelled gene discovery but face certain drawbacks with regards to prokaryotic genome annotation. Identification of transcriptional start sites, demarcating overlapping gene boundaries, and identifying regulatory elements such as small RNA are not accurate using these approaches. In this study, we re-visit the structural annotation of Mannheimia haemolytica PHL213, a bovine respiratory disease pathogen. M. haemolytica is one of the causative agents of bovine respiratory disease that results in about $3 billion annual losses to the cattle industry. We used RNA-Seq and analyzed the data using freely-available computational methods and resources. The aim was to identify previously unannotated regions of the genome using RNA-Seq based expression profile to complement the existing annotation of this pathogen.

resultsUsing the Illumina Genome Analyzer, we generated 9,055,826 reads (average length ~76 bp) and aligned them to the reference genome using Bowtie. The transcribed regions were analyzed using SAMTOOLS and custom Perl scripts in conjunction with BLAST searches and available gene annotation information. The single nucleotide resolution map enabled the identification of 14 novel protein coding regions as well as 44 potential novel sRNA. The basal transcription profile revealed that 2,506 of the 2,837 annotated regions were expressed in vitro, at 95.25% coverage, representing all broad functional gene categories in the genome. The expression profile also helped identify 518 potential operon structures involving 1,086 co-expressed pairs. We also identified 11 proteins with mutated/alternate start codons.

conclusionsThe application of RNA-Seq based transcriptome profiling to structural gene annotation helped correct existing annotation errors and identify potential novel protein coding regions and sRNA. We used computational tools to predict regulatory elements such as promoters and terminators associated with the novel expressed regions for further characterization of these novel functional elements. Our study complements the existing structural annotation of Mannheimia haemolytica PHL213 based on experimental evidence. Given the role of sRNA in virulence gene regulation and stress response, potential novel sRNA described in this study can form the framework for future studies to determine the role of sRNA, if any, in M. haemolytica pathogenesis.

Indexed as

TranscriptomeAnimalsCattleCattle DiseasesComputational BiologyGene Expression ProfilingGenome, BacterialMannheimia haemolyticaMolecular Sequence AnnotationOpen Reading FramesOperonRespiratory Tract DiseasesRNA, BacterialSequence AlignmentSequence Analysis, RNARNA, Bacterial

Identifiers

PMID23046475
PMCPMC3439734
OpenAlexW2063594437

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.