Evidence map›Paper›PMID 36896580›Full record

SynthesisThe plant genome2023

Meta-QTL s and haplotypes for efficient zinc biofortification of rice.

Gaurav Joshi, Yan Paing Soe, Alvin Palanog, Tapas Kumer Hore, Chau Thanh Nha, Mark Ian Calayugan, Mary Ann Inabangan-Asilo, Amery Amparado, Indra Deo Pandey, Pompe C Sta Cruz and 2 more

Open access · goldAbstract readMeta-Analysis
In one paragraph

Synthesis in The plant genome, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed, 2 pooled it
16.3field-weighted citation impact, top 1% 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

16 citing papers in PubMed, 2 syntheses or guidelines pooled it, 33 citations in OpenAlex.

  1. Pooled it
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  13. Genomic prediction and QTL analysis for grain Zn content and yield inJournal of plant biochemistry and biotechnology · 2024
    Article
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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

12 authors at 6 institutions in 4 countries.

Gaurav JoshiRice Genetic Design and Validation Unit, International Rice Research Institute, Los Baños, Philippines.
Yan Paing SoeDepartment of Agriculture, Nay Pyi Taw, Myanmar.
Alvin PalanogCan Tho University (CTU), Can Tho, Vietnam.
Tapas Kumer HoreRice Genetic Design and Validation Unit, International Rice Research Institute, Los Baños, Philippines.
Chau Thanh NhaPhilippines Rice Research Institute, Muñoz, Nueva Ecija, Philippines.
Mark Ian CalayuganUniversity of the Philippines, Los Banos, Laguna, Philippines.
Mary Ann Inabangan-AsiloRice Genetic Design and Validation Unit, International Rice Research Institute, Los Baños, Philippines.
Amery AmparadoRice Genetic Design and Validation Unit, International Rice Research Institute, Los Baños, Philippines.
Indra Deo PandeyGovind Ballabh Pant University of Agriculture and Technology, Pantnagar, Uttarakhand, India.
Pompe C Sta CruzUniversity of the Philippines, Los Banos, Laguna, Philippines.
Jose E HernandezUniversity of the Philippines, Los Banos, Laguna, Philippines.
B P Mallikarjuna SwamyRice Genetic Design and Validation Unit, International Rice Research Institute, Los Baños, Philippines.ORCID 0000-0003-3125-4225
International Rice Research Institute · PHUniversity of the Philippines Los Baños · PHCan Tho University · VNGovind Ballabh Pant University of Agriculture and Technology · INMinistry of Health and Sports · MMPhilippine Rice Research Institute · PH

Funding

Gates Foundation
6 · The paper itself

Abstract

Biofortification of rice with improved grain zinc (Zn) content is the most sustainable and cost-effective approach to address Zn malnutrition in Asia. Genomics-assisted breeding using precise and consistent Zn quantitative trait loci (QTLs), genes, and haplotypes can fast-track the development of Zn biofortified rice varieties. We conducted the meta-analysis of 155 Zn QTLs reported from 26 different studies. Results revealed 57 meta-QTLs with a significant reduction of 63.2% and 80% in the number and confidence interval of the Zn QTLs, respectively. Meta-quantitative trait loci (MQTLs) regions were found to be enriched with diverse metal homeostasis genes; at least 11 MQTLs were colocated with 20 known major genes involved in the production of root exudates, metal uptake, transport, partitioning, and loading into grains in rice. These genes were differentially expressed in vegetative and reproductive tissues, and a complex web of interactions were observed among them. We identified superior haplotypes and their combinations for nine candidate genes (CGs), and the frequency and allelic effects of superior haplotypes varied in different subgroups. The precise MQTLs with high phenotypic variance, CGs, and superior haplotypes identified in our study are useful for an efficient Zn biofortification of rice and to ensure Zn as an essential component of all the future rice varieties through mainstreaming of Zn breeding.

Indexed as

OryzaQuantitative Trait LociBiofortificationHaplotypesPlant BreedingZincZinc

Identifiers

PMID36896580
PMCPMC12807186
OpenAlexW4323812725

What Socratic 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 Socratic graph.