Evidence map›Paper›PMID 32764649›Full record

ArticleScientific reports2020

Comparative assessment of genetic diversity matrices and clustering methods in white Guinea yam (Dioscorea rotundata) based on morphological and molecular markers.

Kwabena Darkwa, Paterne Agre, Bunmi Olasanmi, Kohtaro Iseki, Ryo Matsumoto, Adrian Powell, Guillaume Bauchet, David De Koeyer, Satoru Muranaka, Patrick Adebola and 3 more

Abstract readComparative Study
In one paragraph

Article in Scientific reports, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.

0numbers the graph read from it
0cells of the map it votes in
22citing 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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3 · Its place in the literature

Who cites it

22 citing papers in PubMed.

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  11. Characterization ofFrontiers in plant science · 2023
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  15. Article
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  17. Diversity of Water Yam (Plants (Basel, Switzerland) · 2021
    Article
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  19. Article
  20. 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

13 authors.

Kwabena DarkwaInternational Institute of Tropical Agriculture (IITA), Ibadan, Nigeria.
Paterne AgreInternational Institute of Tropical Agriculture (IITA), Ibadan, Nigeria.
Bunmi OlasanmiDepartment of Agronomy, University of Ibadan, Ibadan, Nigeria.
Kohtaro IsekiJapan International Research Center for Agricultural Sciences, Tsukuba, Japan.
Ryo MatsumotoInternational Institute of Tropical Agriculture (IITA), Ibadan, Nigeria.
Adrian PowellBoyce Thompson Institute, Ithaca, NY, USA.
Guillaume BauchetBoyce Thompson Institute, Ithaca, NY, USA.
David De KoeyerAgriculture and Agri-Food Canada, 850 Lincoln Road, Fredericton, NB, E3B 4Z7, Canada.
Satoru MuranakaJapan International Research Center for Agricultural Sciences, Tsukuba, Japan.
Patrick AdebolaInternational Institute of Tropical Agriculture (IITA), Abuja, Nigeria.
Robert AsieduInternational Institute of Tropical Agriculture (IITA), Ibadan, Nigeria.
Ryohei TerauchiIwate Biotechnology Research Center, Kitakami, Iwate, Japan.
Asrat AsfawInternational Institute of Tropical Agriculture (IITA), Ibadan, Nigeria. A.Amele@cgiar.org.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Understanding the diversity and genetic relationships among and within crop germplasm is invaluable for genetic improvement. This study assessed genetic diversity in a panel of 173 D. rotundata accessions using joint analysis for 23 morphological traits and 136,429 SNP markers from the whole-genome resequencing platform. Various diversity matrices and clustering methods were evaluated for a comprehensive characterization of genetic diversity in white Guinea yam from West Africa at phenotypic and molecular levels. The translation of the different diversity matrices from the phenotypic and genomic information into distinct groups varied with the hierarchal clustering methods used. Gower distance matrix based on phenotypic data and identity by state (IBS) distance matrix based on SNP data with the UPGMA clustering method found the best fit to dissect the genetic relationship in current set materials. However, the grouping pattern was inconsistent (r = - 0.05) between the morphological and molecular distance matrices due to the non-overlapping information between the two data types. Joint analysis for the phenotypic and molecular information maximized a comprehensive estimate of the actual diversity in the evaluated materials. The results from our study provide valuable insights for measuring quantitative genetic variability for breeding and genetic studies in yam and other root and tuber crops.

Indexed as

Genetic VariationDioscoreaGenetic MarkersPhenotypeGenetic Markers

Identifiers

PMID32764649
PMCPMC7413250

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