Evidence map›Paper›PMID 24861452›Full record

ArticleMolecular biology reports2014

Association mapping of agro-morphological characters among the global collection of finger millet genotypes using genomic SSR markers.

B Kalyana Babu, P K Agrawal, Dinesh Pandey, J P Jaiswal, Anil Kumar

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Article in Molecular biology reports, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

Who cites it

16 citing papers in PubMed.

  1. Improvement of millets in the post-genomic era.Physiology and molecular biology of plants : an international journal of functional plant biology · 2022
    Review
  2. Genetics and breeding for climate change in Orphan crops.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2021
    Review
  3. Article
  4. Review
  5. Review
  6. Review
  7. Article
  8. Article
  9. Finger Millet [Frontiers in plant science · 2018
    Review
  10. Article
  11. Article
  12. Review
  13. Gene Discovery and Advances in Finger Millet [Frontiers in plant science · 2016
    Review
  14. Article
  15. Article
  16. Review
4 · The record

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5 · Who and what money

Authors and funding

5 authors.

B Kalyana BabuDepartment of Molecular Biology and Genetic Engineering, College of Basic Sciences & Humanities, G.B. Pant University of Agriculture and Technology, Pantnagar, 263-145, India, kalyan_biotek@yahoo.co.in.
P K Agrawal
Dinesh Pandey
J P Jaiswal
Anil Kumar

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Identification of alleles responsible for various agro-morphological characters is a major concern to further improve the finger millet germplasm. Forty-six genomic SSRs were used for genetic analysis and population structure analysis of a global collection of 190 finger millet genotypes and fifteen agro-morphological characters were evaluated. The overall results showed that Asian genotypes were smaller in height, smaller flag leaf length, less basal tiller number, early flowering and early maturity nature, small ear head length, and smaller in length of longest finger. The 46 SSRs yielded 90 scorable alleles and the polymorphism information content values varied from 0.292 to 0.703 at an average of 0.442. The gene diversity was in the range of 0.355 to 0.750 with an average value of 0.528. The 46 genomic SSR loci grouped the 190 finger millet genotypes into two major clusters based on their geographical origin by the both phylogenetic clustering and population structure analysis by STRUCTURE software. Association mapping of QTLs for 15 agro-morphological characters with 46 genomic SSRs resulted in identification of five markers were linked to QTLs of four traits at a significant threshold (P) level of ≤ 0.01 and ≤ 0.001. The QTL for basal tiller number was strongly associated with the locus UGEP81 at a P value of 0.001 by explaining the phenotypic variance (R (2)) of 10.8%. The QTL for days to 50% flowering was linked by two SSR loci UGEP77 and UGEP90, explained 10 and 8.7% of R (2) respectively at a P value of 0.01. The SSR marker, FM9 found to have strong association to two agro-morphological traits, flag leaf width (P-0.001, R(2)-14.1 %) and plant height (P-0.001, R(2)-11.2%). The markers linked to the QTLs for above agro-morphological characters found in the present study can be further used for cloning of the full length gene, fine mapping and their further use in the marker assisted breeding programmes for introgression of alleles into locally well adapted germplasm.

Indexed as

Chromosome MappingGenotypeMicrosatellite RepeatsAllelesDNA, PlantEleusineGenomicsIndiaPhenotypePhylogenyPhylogeographyPolymorphism, GeneticQuantitative Trait LociDNA, Plant

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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.