Evidence map›Paper›PMID 28295044›Full record

ArticleScientific reports2017

Novel transcriptome assembly and comparative toxicity pathway analysis in mahi-mahi (Coryphaena hippurus) embryos and larvae exposed to Deepwater Horizon oil.

Elvis Genbo Xu, Edward M Mager, Martin Grosell, E Starr Hazard, Gary Hardiman, Daniel Schlenk

Abstract read
In one paragraph

Article in Scientific reports, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
–field-weighted citation impact
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

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3 · Its place in the literature

Who cites it

6 citing papers in PubMed.

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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.

Elvis Genbo XuDepartment of Environmental Sciences, University of California, Riverside, CA 92521, USA.
Edward M MagerDepartment of Biological Sciences, University of North Texas, Denton, TX 76203, USA.
Martin GrosellDepartment of Marine Biology and Ecology, University of Miami, Miami, FL 33149, USA.
E Starr HazardCenter for Genomic Medicine, Medical University of South Carolina, Charleston, SC 29403, USA.
Gary HardimanCenter for Genomic Medicine, Medical University of South Carolina, Charleston, SC 29403, USA.
Daniel SchlenkDepartment of Environmental Sciences, University of California, Riverside, CA 92521, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The impacts of Deepwater Horizon (DWH) oil on morphology and function during embryonic development have been documented for a number of fish species, including the economically and ecologically important pelagic species, mahi-mahi (Coryphaena hippurus). However, further investigations on molecular events and pathways responsible for developmental toxicity have been largely restricted due to the limited molecular data available for this species. We sought to establish the de novo transcriptomic database from the embryos and larvae of mahi-mahi exposed to water accommodated fractions (HEWAFs) of two DWH oil types (weathered and source oil), in an effort to advance our understanding of the molecular aspects involved during specific toxicity responses. By high throughput sequencing (HTS), we obtained the first de novo transcriptome of mahi-mahi, with 60,842 assembled transcripts and 30,518 BLAST hits. Among them, 2,345 genes were significantly regulated in 96hpf larvae after exposure to weathered oil. With comparative analysis to a reference-transcriptome-guided approach on gene ontology and tox-pathways, we confirmed the novel approach effective for exploring tox-pathways in non-model species, and also identified a list of co-expressed genes as potential biomarkers which will provide information for the construction of an Adverse Outcome Pathway which could be useful in Ecological Risk Assessments.

Indexed as

AnimalsEmbryonic DevelopmentEmbryo, NonmammalianLarvaPerciformesPetroleumPetroleum PollutionPolycyclic Aromatic HydrocarbonsSeafoodTranscriptomeWater Pollutants, ChemicalPetroleumPolycyclic Aromatic HydrocarbonsWater Pollutants, Chemical

Identifiers

PMID28295044
PMCPMC5353654

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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.