Evidence map›Paper›PMID 42918879›Full record

ReviewTAG. Theoretical and applied genetics. Theoretische und angewandte Genetik2026

Superior haplotypes for transforming crop breeding.

Nandigam Vinay Kumar, Ajay Bogati, Uma Maheshwar Singh, A Prasanna Rajesh, T Srinivas, Ajay Kohli, Sanjay Kalia, Arvind Kumar, Pallavi Sinha, Vikas Kumar Singh

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In one paragraph

Review in TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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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

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3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

10 authors.

Nandigam Vinay KumarInternational Rice Research Institute, Los Banos, Philippines.
Ajay BogatiInternational Rice Research Institute, Los Banos, Philippines.
Uma Maheshwar SinghInternational Rice Research Institute, Los Banos, Philippines.
A Prasanna RajeshAcharya N.G. Ranga Agricultural University, Bapatla, India.
T SrinivasAcharya N.G. Ranga Agricultural University, Bapatla, India.
Ajay KohliInternational Rice Research Institute, Los Banos, Philippines.
Sanjay KaliaDepartment of Biotechnology, CGO Complex, Lodhi Road, New Delhi, India.
Arvind KumarInternational Rice Research Institute, Los Banos, Philippines.
Pallavi SinhaInternational Rice Research Institute, Los Banos, Philippines. p.sinha@cgiar.org.
Vikas Kumar SinghInternational Rice Research Institute, Los Banos, Philippines. v.k.singh@cgiar.org.ORCID http://orcid.org/0000-0002-1560-1648

Funding

Department of Biotechnology, Government of India BT/PR32853/AGill/103/1159/2019
6 · The paper itself

Abstract

key messageA standardized superior haplotype framework, validated across cereals, oilseeds and legumes, resolves genetic architecture overlooked by the SNP-based approach and guides targeted breeding for developing climate-resilient crops. Climate change and the rapid rise in the global population are exerting immense pressure on limited natural and genetic resources. Meeting future food demands requires accelerated genetic gain under rapidly changing environmental conditions. Advances in genomics, supported by large-scale sequencing of diverse crop germplasm, have enabled the mapping of key genes and the development of climate-resilient varieties. However, the utility of these genes and their associated haplotypes is often limited, as they are specific to particular ecologies and populations, restricting their broader introgression into various breeding programmes. The concept of superior haplotypes can help us address these limitations by identifying the allelic combination that confers a desirable trait with stable, consistent and significant performance across diverse panels and environments. For instance, in rice, the GS3-H1 haplotype is associated with improved grain size and yield potential, while Sub1A-1 confers superior submergence tolerance compared to Sub1A-2. Similarly, in rapeseed, Hap1 of qOCA3 and qOCC6 is associated with higher oil content. Building on such examples, this review systematically catalogues superior haplotypes identified across major crops, highlights key research gaps, and outlines a roadmap for their deployment in genomic-assisted breeding to enhance crop productivity, adaptability, and resilience.

Indexed as

Crops, AgriculturalHaplotypesPlant BreedingPhenotypePolymorphism, Single NucleotideQuantitative Trait Loci

Identifiers

What OpenQuestion holds

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Read underepoch 390

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.