Evidence map›Paper›PMID 29891987›Full record

ArticleScientific reports2018

Optimization of Assembly Pipeline may Improve the Sequence of the Chloroplast Genome in Quercus spinosa.

Xiangzhou Zhang, Yong Hu, Mei Liu, Tiange Lang

Abstract read
In one paragraph

Article in Scientific reports, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

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

3 citing papers in PubMed.

  1. Complete Chloroplast Genomes of FiveEcology and evolution · 2026
    Article
  2. Article
  3. Complete Chloroplast Genome Sequence ofLife (Basel, Switzerland) · 2022
    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.

Xiangzhou ZhangBig Data Decision Institute, Jinan University, Tianhe, Guangzhou, P.R. China.ORCID 0000-0003-3752-0045
Yong HuBig Data Decision Institute, Jinan University, Tianhe, Guangzhou, P.R. China.
Mei LiuBig Data Decision Institute, Jinan University, Tianhe, Guangzhou, P.R. China.
Tiange LangBig Data Decision Institute, Jinan University, Tianhe, Guangzhou, P.R. China. langtiange@xtbg.org.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Obtaining chloroplast (cp) genome sequence is necessary for studying physiological roles in plants. However, it is difficult to use traditional sequencing methods to get cp genome sequences because of the complex procedures of preparing templates. With the advent of next-generation sequencing technology, massive genome sequences can be produced. Thus, a good pipeline to assemble next-generation sequence reads with optimized k-mer length is essential to get whole cp genome sequences. Moreover, adjustment of other parameters is also very important, especially for the assembly of the cp genome. In this study, we developed a pipeline to generate the cp genome for Quercus spinosa. When Quercus rubra was used as a reference, we achieved coverage of 97.75% after optimizing k-mer length as well as other parameters. The efficiency of the pipeline makes it a useful method for cp genome construction in plants. It also provides great perspective on the analysis of cp genome characteristics and evolution.

Indexed as

Genome, ChloroplastComputational BiologyDNA, ChloroplastHigh-Throughput Nucleotide SequencingQuercusSequence Analysis, DNADNA, Chloroplast

Identifiers

PMID29891987
PMCPMC5995970

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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.