Evidence map›Paper›PMID 30598864›Full record

ArticleApplications in plant sciences2018

Transcriptome analysis of maca (

Rui-Guang Shang, Pu Yang, Bing-Yi Wang, Zun-Ling Zhao

Open access · goldAbstract read
In one paragraph

Article in Applications in plant sciences, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed, 1 pooled it
0.2field-weighted citation impact, top 45% 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

6 citing papers in PubMed, 1 synthesis or guideline pooled it, 5 citations in OpenAlex.

  1. Pooled it
  2. Review
  3. Review
  4. Plant signaling & behavior · 2022
    Article
  5. Article
  6. Transcriptome analysis of maca (Applications in plant sciences · 2018
    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

4 authors at 1 institution in 1 country.

Rui-Guang ShangResearch Institute of Resource Insects Chinese Academy of Forestry Kunming 650224 Yunnan People's Republic of China.ORCID 0000-0001-5307-3121
Pu YangResearch Institute of Resource Insects Chinese Academy of Forestry Kunming 650224 Yunnan People's Republic of China.
Bing-Yi WangResearch Institute of Resource Insects Chinese Academy of Forestry Kunming 650224 Yunnan People's Republic of China.
Zun-Ling ZhaoResearch Institute of Resource Insects Chinese Academy of Forestry Kunming 650224 Yunnan People's Republic of China.
Research Institute of Resource Insects · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

premise of the studyMaca (

methodsRNA-Seq technology was used to compare the transcriptome of black maca root at three developmental stages. Gene Ontology term enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were applied for the identification of pathways in which differentially expressed genes were significantly enriched.

resultsTrinity was used to de novo assemble the reads, and 120,664 unigenes were assembled. Of these, 71.53% of the unigenes were annotated based on BLAST. A total of 18,321 differentially expressed genes were observed. Gene Ontology term enrichment analysis found that the most highly represented pathway among the differentially expressed genes was for genes involved in starch and sucrose metabolism. We also found that genes involved in secondary metabolite biosynthesis, such as glucosinolate biosynthesis, were significantly enriched. DISCUSSION: The genes that were differentially expressed between developmental time points likely reflect both developmental pathways and responses to changes in the environment. As such, the transcriptome data in this study serve as a reference for subsequent mining of genes that are involved in the synthesis of important bioactive components in maca.

Indexed as

Brassicaceaedifferentially expressed genesLepidium meyeniimacaRNA‐Seqsecondary metabolite biosynthesistranscriptome

Identifiers

PMID30598864
PMCPMC6303156
OpenAlexW2904587626

What OpenQuestion holds

Textmetadata
LicenceCC BY
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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.