Evidence map›Paper›PMID 27092945›Full record

ArticlePloS one2016

Combining and Comparing Coalescent, Distance and Character-Based Approaches for Barcoding Microalgaes: A Test with Chlorella-Like Species (Chlorophyta).

Shanmei Zou, Cong Fei, Jiameng Song, Yachao Bao, Meilin He, Changhai Wang

Abstract read
In one paragraph

Article in PloS one, 2016. 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
–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

11 citing papers in PubMed.

  1. MicroalgaeBiology · 2026
    Review
  2. Article
  3. The Diversity of N-Glycans ofFoods (Basel, Switzerland) · 2024
    Article
  4. Article
  5. Identification of Eukaryotic Microalgal Strains.Journal of applied phycology · 2020
    Article
  6. Article
  7. Article
  8. Polyphasic taxonomy of green algae strains isolated from Mediterranean freshwaters.Journal of biological research (Thessalonike, Greece) · 2019
    Article
  9. Article
  10. Article
  11. 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

6 authors.

Shanmei ZouJiangsu Provincial Key Laboratory of Marine Biology, College of Resources and Environmental Science, Nanjing Agricultural University, Nanjing 210095, PR China.
Cong FeiJiangsu Provincial Key Laboratory of Marine Biology, College of Resources and Environmental Science, Nanjing Agricultural University, Nanjing 210095, PR China.
Jiameng SongJiangsu Provincial Key Laboratory of Marine Biology, College of Resources and Environmental Science, Nanjing Agricultural University, Nanjing 210095, PR China.
Yachao BaoJiangsu Provincial Key Laboratory of Marine Biology, College of Resources and Environmental Science, Nanjing Agricultural University, Nanjing 210095, PR China.
Meilin HeJiangsu Provincial Key Laboratory of Marine Biology, College of Resources and Environmental Science, Nanjing Agricultural University, Nanjing 210095, PR China.
Changhai WangJiangsu Provincial Key Laboratory of Marine Biology, College of Resources and Environmental Science, Nanjing Agricultural University, Nanjing 210095, PR China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Several different barcoding methods of distinguishing species have been advanced, but which method is the best is still controversial. Chlorella is becoming particularly promising in the development of second-generation biofuels. However, the taxonomy of Chlorella-like organisms is easily confused. Here we report a comprehensive barcoding analysis of Chlorella-like species from Chlorella, Chloroidium, Dictyosphaerium and Actinastrum based on rbcL, ITS, tufA and 16S sequences to test the efficiency of traditional barcoding, GMYC, ABGD, PTP, P ID and character-based barcoding methods. First of all, the barcoding results gave new insights into the taxonomic assessment of Chlorella-like organisms studied, including the clear species discrimination and resolution of potentially cryptic species complexes in C. sorokiniana, D. ehrenbergianum and C. Vulgaris. The tufA proved to be the most efficient barcoding locus, which thus could be as potential "specific barcode" for Chlorella-like species. The 16S failed in discriminating most closely related species. The resolution of GMYC, PTP, P ID, ABGD and character-based barcoding methods were variable among rbcL, ITS and tufA genes. The best resolution for species differentiation appeared in tufA analysis where GMYC, PTP, ABGD and character-based approaches produced consistent groups while the PTP method over-split the taxa. The character analysis of rbcL, ITS and tufA sequences could clearly distinguish all taxonomic groups respectively, including the potentially cryptic lineages, with many character attributes. Thus, the character-based barcoding provides an attractive complement to coalescent and distance-based barcoding. Our study represents the test that proves the efficiency of multiple DNA barcoding in species discrimination of microalgaes.

Indexed as

ChlorellaDNA Barcoding, TaxonomicMicroalgaePhylogeny

Identifiers

PMID27092945
PMCPMC4841637

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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.