Evidence map›Paper›PMID 26702399›Full record

ArticleMeta gene2016

De novo assembly and characterization of tissue-specific transcriptome in the endangered golden mahseer, Tor putitora.

Ashoktaru Barat, Rohit Kumar, Chirag Goel, Atul Kumar Singh, Prabhati Kumari Sahoo

Abstract read
In one paragraph

Article in Meta gene, 2016. 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
1 · What the graph read from it

What it found

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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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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.

  1. Article
  2. Full-Length Transcriptome Analysis of Four Different Tissues ofInternational journal of molecular sciences · 2021
    Article
  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

5 authors.

Ashoktaru BaratICAR-Directorate of Coldwater Fisheries Research, Bhimtal, Nainital 263136, Uttarakhand, India.
Rohit KumarICAR-Directorate of Coldwater Fisheries Research, Bhimtal, Nainital 263136, Uttarakhand, India.
Chirag GoelICAR-Directorate of Coldwater Fisheries Research, Bhimtal, Nainital 263136, Uttarakhand, India.
Atul Kumar SinghICAR-Directorate of Coldwater Fisheries Research, Bhimtal, Nainital 263136, Uttarakhand, India.
Prabhati Kumari SahooICAR-Directorate of Coldwater Fisheries Research, Bhimtal, Nainital 263136, Uttarakhand, India.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The golden mahseer (Tor putitora) graces most of the Himalayan Rivers of India and neighboring South Asian countries. Despite its several importance as a research model, as food, and in sport fishing, knowledge on transcriptome database is nil. Therefore, it was targeted to develop reference transcriptome databases of the species using next-generation sequencing. In the present study, 100,540,130 high-quality paired-end reads were obtained from six cDNA libraries of spleen, liver, gill, kidney, muscle, and brain with 28.4 GB data using Illumina paired-end sequencing technology. Tissue-specific transcriptomes as well as complete transcriptome assembly were analyzed for concise representation of the study. In brief, the de novo assembly of individual tissue resulted in an average of 31,829 (18,512-46,348) contigs per sample, while combined transcriptome comprised 77,907 unique transcript fragments (unigenes) assembled from reads of six tissues. Approximately 75,407 (96.8%) unigenes could be annotated according to their homology matches in the nr, SwisseProt, GO, or KEGG databases. Comparative analysis showed that 84% of the unigenes have significant similarity to zebra fish RefSeq proteins. Tissue-specific-dominated genes were also identified to hypothesize their localization and expression in individual tissue. In addition, 2485 simple sequence repeats (SSRs) were detected from 77,907 transcripts in the combined transcriptome of the golden mahseer. This study has generated organ-specific transcriptome profiles, which will be helpful to understand the local adaptation, genome evolution, and also future functional studies on immune system of the golden mahseer.

Indexed as

EndangeredGolden mahseerOrgan-specific transcriptomeSSR markers

Identifiers

PMID26702399
PMCPMC4669534

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Registered trials

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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.