Evidence map›Paper›PMID 24367635›Full record

ArticlePloS one2013

Comparison of SSR and SNP markers in estimation of genetic diversity and population structure of Indian rice varieties.

Nivedita Singh, Debjani Roy Choudhury, Amit Kumar Singh, Sundeep Kumar, Kalyani Srinivasan, R K Tyagi, N K Singh, Rakesh Singh

Open access · goldAbstract readComparative Study
In one paragraph

Article in PloS one, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 99 papers.

0numbers the graph read from it
0cells of the map it votes in
99citing papers in PubMed
6.7field-weighted citation impact, top 3% of its field
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

99 citing papers in PubMed, 249 citations in OpenAlex.

  1. Development of SNPs for Crop Improvement.Methods in molecular biology (Clifton, N.J.) · 2027
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39 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

8 authors at 2 institutions in 1 country.

Nivedita SinghDivision of Genomic Resources, National Bureau of Plant Genetic Resources, New Delhi, Delhi, India.
Debjani Roy ChoudhuryDivision of Genomic Resources, National Bureau of Plant Genetic Resources, New Delhi, Delhi, India.
Amit Kumar SinghDivision of Genomic Resources, National Bureau of Plant Genetic Resources, New Delhi, Delhi, India.
Sundeep KumarDivision of Genomic Resources, National Bureau of Plant Genetic Resources, New Delhi, Delhi, India.
Kalyani SrinivasanGermplasm Conservation Division, National Bureau of Plant Genetic Resources, New Delhi, Delhi, India.
R K TyagiGermplasm Conservation Division, National Bureau of Plant Genetic Resources, New Delhi, Delhi, India.
N K SinghNational Research Centre on Plant Biotechnology, Indian Agricultural Research Institute, New Delhi, Delhi, India.
Rakesh SinghDivision of Genomic Resources, National Bureau of Plant Genetic Resources, New Delhi, Delhi, India.
National Bureau of Plant Genetic Resources · INIndian Agricultural Research Institute · IN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Simple sequence repeat (SSR) and Single Nucleotide Polymorphic (SNP), the two most robust markers for identifying rice varieties were compared for assessment of genetic diversity and population structure. Total 375 varieties of rice from various regions of India archived at the Indian National GeneBank, NBPGR, New Delhi, were analyzed using thirty six genetic markers, each of hypervariable SSR (HvSSR) and SNP which were distributed across 12 rice chromosomes. A total of 80 alleles were amplified with the SSR markers with an average of 2.22 alleles per locus whereas, 72 alleles were amplified with SNP markers. Polymorphic information content (PIC) values for HvSSR ranged from 0.04 to 0.5 with an average of 0.25. In the case of SNP markers, PIC values ranged from 0.03 to 0.37 with an average of 0.23. Genetic relatedness among the varieties was studied; utilizing an unrooted tree all the genotypes were grouped into three major clusters with both SSR and SNP markers. Analysis of molecular variance (AMOVA) indicated that maximum diversity was partitioned between and within individual level but not between populations. Principal coordinate analysis (PCoA) with SSR markers showed that genotypes were uniformly distributed across the two axes with 13.33% of cumulative variation whereas, in case of SNP markers varieties were grouped into three broad groups across two axes with 45.20% of cumulative variation. Population structure were tested using K values from 1 to 20, but there was no clear population structure, therefore Ln(PD) derived Δk was plotted against the K to determine the number of populations. In case of SSR maximum Δk was at K=5 whereas, in case of SNP maximum Δk was found at K=15, suggesting that resolution of population was higher with SNP markers, but SSR were more efficient for diversity analysis.

Indexed as

Microsatellite RepeatsPhylogenyPolymorphism, Single NucleotideGenetic MarkersIndiaOryzaPopulation DynamicsStatistics as TopicGenetic Markers

Identifiers

PMID24367635
PMCPMC3868579
OpenAlexW2071125117

What OpenQuestion holds

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LicenceCC BY
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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.