Evidence map›Paper›PMID 20376514›Full record

ArticleFunctional & integrative genomics2010

Identification of candidate genes for grain number in rice (Oryza sativa L.).

Rupesh Deshmukh, Abhinay Singh, Neha Jain, Shweta Anand, Raju Gacche, Ashok Singh, Kishor Gaikwad, Tilak Sharma, Trilochan Mohapatra, Nagendra Singh

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Article in Functional & integrative genomics, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers.

0numbers the graph read from it
0cells of the map it votes in
29citing 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

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

29 citing papers in PubMed.

  1. Article
  2. Plants (Basel, Switzerland) · 2025
    Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Natural variation ofFrontiers in plant science · 2022
    Article
  9. Article
  10. Article
  11. Ionomic Approaches for Discovery of Novel Stress-Resilient Genes in Plants.International journal of molecular sciences · 2021
    Review
  12. Molecular and Genetic Aspects of Grain Number Determination in Rice (International journal of molecular sciences · 2021
    Review
  13. Review
  14. Article
  15. Review
  16. Article
  17. Characterisation of a novel quantitative trait locus, GN4-1, for grain number and yield in rice (Oryza sativa L.).TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2018
    Article
  18. Article
  19. Article
  20. Article
4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

10 authors.

Rupesh DeshmukhRice Genome Laboratory, National Research Centre on Plant Biotechnology, New Delhi, 110012, India.
Abhinay Singh
Neha Jain
Shweta Anand
Raju Gacche
Ashok Singh
Kishor Gaikwad
Tilak Sharma
Trilochan Mohapatra
Nagendra Singh

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Large number of well-filled grains per panicle is an important yield component trait in rice. A combination of QTL mapping and transcriptome profiling was used to identify candidate genes for grain number. A framework linkage map was constructed using 166 SSR markers evenly distributed over the 12 rice chromosomes. QTL mapping using 3 years phenotyping data on a set of recombinant inbred lines derived from a cross between Pusa 1266 (high grain number) and Pusa Basmati 1 (low grain number) identified one consistent QTL qGN4-1 on the long arm of chromosome 4 with major effect on grain number. This QTL was co-localized with major QTLs for primary and secondary branches per panicle, and number of panicles per plant. The QTL interval was narrowed down to 11.1 cM (0.78 Mbp) by targeted enrichment of the region with six additional markers. Microarray transcriptome profiling revealed eight genes in the qGN4-1 region differentially expressed between the two parents during early panicle development. Synteny of this QTL and potential candidates was examined in wheat, barley, maize, sorghum, and Brachypodium to further validate the association.

Indexed as

Chromosome SegregationChromosomes, PlantElectrophoresis, Agar GelGene Expression ProfilingGene Expression Regulation, PlantGenes, PlantInbreedingOligonucleotide Array Sequence AnalysisOryzaPromoter Regions, GeneticQuantitative Trait, HeritableQuantitative Trait LociSeeds

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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.