Evidence map›Paper›PMID 28066449›Full record

ReviewFrontiers in plant science2016

QTLomics in Soybean: A Way Forward for Translational Genomics and Breeding.

Giriraj Kumawat, Sanjay Gupta, Milind B Ratnaparkhe, Shivakumar Maranna, Gyanesh K Satpute

Abstract readReview
In one paragraph

Review in Frontiers in plant science, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing 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

13 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. AInternational journal of genomics · 2024
    Article
  5. Article
  6. Review
  7. Prospects of genetics and breeding for low-phosphate tolerance: an integrated approach from soil to cell.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2022
    Review
  8. Review
  9. Article
  10. Review
  11. A Major and Stable Quantitative Trait LocusFrontiers in genetics · 2021
    Article
  12. Article
  13. 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

5 authors.

Giriraj KumawatCrop Improvement Section, ICAR-Indian Institute of Soybean Research Indore, India.
Sanjay GuptaCrop Improvement Section, ICAR-Indian Institute of Soybean Research Indore, India.
Milind B RatnaparkheCrop Improvement Section, ICAR-Indian Institute of Soybean Research Indore, India.
Shivakumar MarannaCrop Improvement Section, ICAR-Indian Institute of Soybean Research Indore, India.
Gyanesh K SatputeCrop Improvement Section, ICAR-Indian Institute of Soybean Research Indore, India.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Food legumes play an important role in attaining both food and nutritional security along with sustainable agricultural production for the well-being of humans globally. The various traits of economic importance in legume crops are complex and quantitative in nature, which are governed by quantitative trait loci (QTLs). Mapping of quantitative traits is a tedious and costly process, however, a large number of QTLs has been mapped in soybean for various traits albeit their utilization in breeding programmes is poorly reported. For their effective use in breeding programme it is imperative to narrow down the confidence interval of QTLs, to identify the underlying genes, and most importantly allelic characterization of these genes for identifying superior variants. In the field of functional genomics, especially in the identification and characterization of gene responsible for quantitative traits, soybean is far ahead from other legume crops. The availability of genic information about quantitative traits is more significant because it is easy and effective to identify homologs than identifying shared syntenic regions in other crop species. In soybean, genes underlying QTLs have been identified and functionally characterized for phosphorous efficiency, flowering and maturity, pod dehiscence, hard-seededness, α-Tocopherol content, soybean cyst nematode, sudden death syndrome, and salt tolerance. Candidate genes have also been identified for many other quantitative traits for which functional validation is required. Using the sequence information of identified genes from soybean, comparative genomic analysis of homologs in other legume crops could discover novel structural variants and useful alleles for functional marker development. The functional markers may be very useful for molecular breeding in soybean and harnessing benefit of translational research from soybean to other leguminous crops. Thus, soybean crop can act as a model crop for translational genomics and breeding of quantitative traits in legume crops. In this review, we summarize current status of identification and characterization of genes underlying QTLs for various quantitative traits in soybean and their significance in translational genomics and breeding of other legume crops.

Indexed as

allelescomparative genomicsfunctional markersgeneshaplotypelegumesquantitative traits

Identifiers

PMID28066449
PMCPMC5174554

What OpenQuestion holds

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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.