Evidence map›Paper›PMID 37975911›Full record

ReviewTAG. Theoretical and applied genetics. Theoretische und angewandte Genetik2023

Meta-QTL analysis in wheat: progress, challenges and opportunities.

Divya Sharma, Anita Kumari, Priya Sharma, Anupma Singh, Anshu Sharma, Zahoor Ahmad Mir, Uttam Kumar, Sofora Jan, M Parthiban, Reyazul Rouf Mir and 10 more

Abstract readReview
PubMed Publisher
In one paragraph

Review in TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed, 3 pooled it
8.7field-weighted citation impact, top 3% of its field
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

14 citing papers in PubMed, 3 syntheses or guidelines pooled it, 22 citations in OpenAlex.

  1. Pooled it
  2. Pooled it
  3. Pooled it
  4. Article
  5. Review
  6. Frontiers in plant science · 2026
    Article
  7. Article
  8. Article
  9. Characterization of a stable QTL for quality-related traits and its effects on yields in wheat (Triticum aestivum L.).TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2025
    Article
  10. Article
  11. Article
  12. Review
  13. Article
  14. 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

20 authors at 6 institutions in 1 country.

Divya SharmaICAR-National Bureau of Plant Genetic Resources, Pusa Campus, New Delhi, India.
Anita KumariDepartment of Botany, University of Delhi, Delhi, India.
Priya SharmaDepartment of Botany, University of Delhi, Delhi, India.
Anupma SinghICAR-National Bureau of Plant Genetic Resources, Pusa Campus, New Delhi, India.
Anshu SharmaICAR-National Bureau of Plant Genetic Resources, Pusa Campus, New Delhi, India.
Zahoor Ahmad MirICAR-National Bureau of Plant Genetic Resources, Pusa Campus, New Delhi, India.
Uttam KumarBorlaug Institute for South Asia (BISA), Ludhiana, India.
Sofora JanSher-e-Kashmir University of Agricultural Sciences and Technology of Kashmir (SKUAST-K), Srinagar, Kashmir, India.
M ParthibanSher-e-Kashmir University of Agricultural Sciences and Technology of Kashmir (SKUAST-K), Srinagar, Kashmir, India.
Reyazul Rouf MirSher-e-Kashmir University of Agricultural Sciences and Technology of Kashmir (SKUAST-K), Srinagar, Kashmir, India.
Pradeep BhatiBorlaug Institute for South Asia (BISA), Ludhiana, India.
Anjan Kumar PradhanICAR-National Bureau of Plant Genetic Resources, Pusa Campus, New Delhi, India.
Aakash YadavICAR-National Bureau of Plant Genetic Resources, Pusa Campus, New Delhi, India.
Dwijesh Chandra MishraICAR- Indian Agricultural Statistics Research Institute, New Delhi, India.
Neeraj BudhlakotiICAR- Indian Agricultural Statistics Research Institute, New Delhi, India.
Mahesh C YadavICAR-National Bureau of Plant Genetic Resources, Pusa Campus, New Delhi, India.
Kiran B GaikwadDivision of Genetics, Indian Council of Agricultural Research (ICAR)-Indian Agricultural Research Institute, New Delhi, India.
Amit Kumar SinghICAR-National Bureau of Plant Genetic Resources, Pusa Campus, New Delhi, India.
Gyanendra Pratap SinghICAR-National Bureau of Plant Genetic Resources, Pusa Campus, New Delhi, India.
Sundeep KumarICAR-National Bureau of Plant Genetic Resources, Pusa Campus, New Delhi, India. Sundeep.Kumar@icar.gov.in.ORCID http://orcid.org/0000-0001-5917-8290
National Bureau of Plant Genetic Resources · INSher-e-Kashmir University of Agricultural Sciences and Technology of Kashmir · INBorlaug Institute for South Asia · INIndian Agricultural Statistics Research Institute · INUniversity of Delhi · INIndian Council of Agricultural Research · IN

Funding

DBT BT/Ag/Network/Wheat/2019-20
6 · The paper itself

Abstract

Wheat, an important cereal crop globally, faces major challenges due to increasing global population and changing climates. The production and productivity are challenged by several biotic and abiotic stresses. There is also a pressing demand to enhance grain yield and quality/nutrition to ensure global food and nutritional security. To address these multifaceted concerns, researchers have conducted numerous meta-QTL (MQTL) studies in wheat, resulting in the identification of candidate genes that govern these complex quantitative traits. MQTL analysis has successfully unraveled the complex genetic architecture of polygenic quantitative traits in wheat. Candidate genes associated with stress adaptation have been pinpointed for abiotic and biotic traits, facilitating targeted breeding efforts to enhance stress tolerance. Furthermore, high-confidence candidate genes (CGs) and flanking markers to MQTLs will help in marker-assisted breeding programs aimed at enhancing stress tolerance, yield, quality and nutrition. Functional analysis of these CGs can enhance our understanding of intricate trait-related genetics. The discovery of orthologous MQTLs shared between wheat and other crops sheds light on common evolutionary pathways governing these traits. Breeders can leverage the most promising MQTLs and CGs associated with multiple traits to develop superior next-generation wheat cultivars with improved trait performance. This review provides a comprehensive overview of MQTL analysis in wheat, highlighting progress, challenges, validation methods and future opportunities in wheat genetics and breeding, contributing to global food security and sustainable agriculture.

Indexed as

Plant BreedingTriticumCrops, AgriculturalEdible GrainPhenotypeQuantitative Trait Loci

Identifiers

PMID37975911
OpenAlexW4388769718

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.