Evidence map›Paper›PMID 39098874›Full record

ArticleScientific reports2024

Deciphering the genetic basis of agronomic, yield, and nutritional traits in rice (Oryza sativa L.) using a saturated GBS-based SNP linkage map.

Mark Ian C Calayugan, Tapas Kumer Hore, Alvin D Palanog, Amery Amparado, Mary Ann Inabangan-Asilo, Gaurav Joshi, Balachiranjeevi Chintavaram, B P Mallikarjuna Swamy

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Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

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4citing papers in PubMed
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1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

8 authors.

Mark Ian C CalayuganRice Breeding and Innovation Department, International Rice Research Institute, DAPO 7777, Metro Manila, Philippines.
Tapas Kumer HoreRice Breeding and Innovation Department, International Rice Research Institute, DAPO 7777, Metro Manila, Philippines.
Alvin D PalanogRice Breeding and Innovation Department, International Rice Research Institute, DAPO 7777, Metro Manila, Philippines.
Amery AmparadoRice Breeding and Innovation Department, International Rice Research Institute, DAPO 7777, Metro Manila, Philippines.
Mary Ann Inabangan-AsiloRice Breeding and Innovation Department, International Rice Research Institute, DAPO 7777, Metro Manila, Philippines.
Gaurav JoshiRice Breeding and Innovation Department, International Rice Research Institute, DAPO 7777, Metro Manila, Philippines.
Balachiranjeevi ChintavaramRice Breeding and Innovation Department, International Rice Research Institute, DAPO 7777, Metro Manila, Philippines.
B P Mallikarjuna SwamyRice Breeding and Innovation Department, International Rice Research Institute, DAPO 7777, Metro Manila, Philippines. m.swamy@irri.org.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Developing high-yielding rice varieties that possess favorable agronomic characteristics and enhanced grain Zn content is crucial in ensuring food security and addressing nutritional needs. This research employed ICIM, IM, and multi-parent population QTL mapping methods to identify important genetic regions associated with traits such as DF, PH, NT, NP, PL, YLD, TGW, GL, GW, Zn, and Fe. Two populations of recombinant inbred lines consisting of 373 lines were phenotyped for agronomic, yield and grain micronutrient traits for three seasons at IRRI, and genotyped by sequencing. Most of the traits demonstrated moderate to high broad-sense heritability. There was a positive relationship between Zn and Fe contents. The principal components and correlation results revealed a significant negative association between YLD and Zn/Fe. ICIM identified 81 QTLs, while IM detected 36 QTLs across populations. The multi-parent population analysis detected 27 QTLs with six of them consistently detected across seasons. We shortlisted eight candidate genes associated with yield QTLs, 19 genes with QTLs for agronomic traits, and 26 genes with Zn and Fe QTLs. Notable candidate genes included CL4 and d35 for YLD, dh1 for DF, OsIRX10, HDT702, sd1 for PH, OsD27 for NP, whereas WFP and OsIPI1 were associated with PL, OsRSR1 and OsMTP1 were associated to TGW. The OsNAS1, OsRZFP34, OsHMP5, OsMTP7, OsC3H33, and OsHMA1 were associated with Fe and Zn QTLs. We identified promising RILs with acceptable yield potential and high grain Zn content from each population. The major effect QTLs, genes and high Zn RILs identified in our study are useful for efficient Zn biofortification of rice.

Indexed as

Chromosome MappingOryzaPolymorphism, Single NucleotideQuantitative Trait LociEdible GrainGenetic LinkageGenotypePhenotypeZincZinc

Identifiers

PMID39098874
PMCPMC11298551

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LicenceCC BY-NC-ND
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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.