Evidence map›Paper›PMID 29321364›Full record

ArticleJournal of genetics2017

Illumina-based de novo transcriptome sequencing and analysis of Chinese forest musk deer.

Zhongxian Xu, Hang Jie, Binlong Chen, Uma Gaur, Nan Wu, Jian Gao, Pinming Li, Guijun Zhao, Dejun Zeng, Mingyao Yang and 1 more

Abstract read
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In one paragraph

Article in Journal of genetics, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
0.7field-weighted citation impact, top 30% 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

11 citing papers in PubMed, 18 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

11 authors at 2 institutions in 1 country.

Zhongxian XuFarm Animal Genetic Resources Exploration and Innovation Key Laboratory of Sichuan Province, Sichuan Agricultural University, Chengdu 611130, People's Republic of China. diyanli@sicau.edu.cn.
Hang Jie
Binlong Chen
Uma Gaur
Nan Wu
Jian Gao
Pinming Li
Guijun Zhao
Dejun Zeng
Mingyao Yang
Diyan Li
Sichuan Agricultural University · CNInstitute of Medicinal Plant Development · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The Chinese forest musk deer (Moschus berezovskii Flerov) is an endangered artiodactyl mammal. The musk secreted by sexually mature males is highly valued for alleged pharmaceutical properties and perfume manufacturing. However, the genomic and transcriptomic resources of musk deer remain deficiently represented and poorly understood. Next-generation sequencing technique is an efficient method for generating an enormous amount of sequence data that can represent a large number of genes and their expression levels. In the present study, we used Illumina HiSeq technology to perform de novo assembly of heart and musk gland transcriptomes from the Chinese forest musk deer. A total of 239,383 transcripts and 176,450 unigenes were obtained, of which 37,329 unigenes were matched to known sequences in the NCBI nonredundant protein (Nr) database; 31,039 unigenes were assigned to 61 GO terms, and 11,782 to 332 KEGG pathways. Additionally, 592 and 2282 differentially expressed genes were found to be specifically expressed in the heart and musk gland, respectively. The abundant transcriptomic data generated in the present report will provide a comprehensive sequence resource for Chinese forest musk deer as well as lay down a foundation which will help in accelerating genetic and functional genomics research in this species.

Indexed as

AnimalsChinaDeerForestsHigh-Throughput Nucleotide SequencingMaleMicrosatellite RepeatsTranscriptome

Identifiers

PMID29321364
OpenAlexW2777157326

What OpenQuestion holds

Textmetadata
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.