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Related Concept Videos

Monohybrid Crosses01:20

Monohybrid Crosses

Overview
Genome-wide Association Studies-GWAS01:11

Genome-wide Association Studies-GWAS

Genome-wide association studies or GWAS are used to identify whether common SNPs are associated with certain diseases. Suppose specific SNPs are more frequently observed in individuals with a particular disease than those without the disease. In that case, those SNPs are said to be associated with the disease. Chi-square analysis is performed to check the probability of the allele likely to be associated with the disease.
GWAS does not require the identification of the target gene involved in...
Trihybrid Crosses02:27

Trihybrid Crosses

Trihybrid Crosses
Some of Mendel’s crosses examined three pairs of contrasting characteristics. Such a cross is called a trihybrid cross. A trihybrid cross is a combination of three individual monohybrid crosses. For example, plant height (tall vs. short), seed shape (round vs. wrinkled), and seed color (yellow vs. green).
The F1 generation plants of a trihybrid cross are heterozygous for all three traits and produce eight gametes. Upon self-fertilization, these gametes have an equal chance to...
Plant Breeding and Biotechnology01:59

Plant Breeding and Biotechnology

Crop cultivation has a long history in human civilization, with records showing the cultivation of cereal plants beginning at around 8000 BC. This early plant breeding was developed primarily to provide a steady supply of food.
Dihybrid Crosses01:18

Dihybrid Crosses

Overview
Law of Independent Assortment02:03

Law of Independent Assortment

While Mendel’s Law of Segregation states that the two alleles for one gene are separated into different gametes, a different question of how different genes are inherited remains. For example, is the gene for tall plants inherited with the gene for green peas? Mendel asked this question by experimenting with a dihybrid cross; a cross in which both parents are homozygous for two distinct traits resulting in an F1 generation that are heterozygous for both traits.

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Breeding by Design for Functional Rice with Genome Editing Technologies
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GWAS and Candidate Gene Prediction of Elemental Accumulation Traits in Rice Using a Multiparental Population.

Qian Zhang1, Tomoyuki Furuta1, Kazunari Kashihara1

  • 1Institute of Plant Science and Resources, Okayama University, 2-20-1 Chuo, Kurashiki, 710-0046, Japan.

Rice (New York, N.Y.)
|May 11, 2026
PubMed
Summary

This study identifies genetic variations influencing 13 essential and non-essential elements in rice straw and grain. It reveals candidate genes for element accumulation, aiding breeding for improved nutritional quality and plant growth.

Keywords:
Oryza sativa L.Element accumulationGWASMulti-parent advanced generation inter-cross populationQTLRice

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Area of Science:

  • Plant Genetics
  • Agricultural Science
  • Nutritional Science

Background:

  • Rice accumulates essential elements for growth and grain nutritional quality.
  • Understanding the genetic basis of elemental accumulation and inter-tissue relationships is crucial for breeding.
  • Existing knowledge on genetic factors controlling multiple element concentrations in rice is limited.

Purpose of the Study:

  • To investigate genetic variations in the concentrations of 13 elements in rice straw and grain.
  • To identify quantitative trait loci (QTLs) and candidate genes associated with elemental accumulation.
  • To provide insights for rice breeding programs aiming to enhance nutritional quality and optimize plant growth.

Main Methods:

  • Utilized a multi-parent advanced generation inter-cross (MAGIC) population derived from eight diverse rice cultivars.
  • Performed comprehensive correlation analysis to evaluate element interrelationships between grain and straw.
  • Conducted haplotype-based genome-wide association studies (GWAS) to identify QTLs and predict candidate genes.

Main Results:

  • Identified genetic variations in 13 elements (P, K, Ca, Mg, As, Cd, Cr, Cu, Fe, Mo, Mn, Ni, Zn) in rice straw and grain.
  • Discovered 104 QTLs (51 in straw, 53 in grain), grouped into 19 clusters and 60 independent QTLs.
  • Predicted 52 candidate genes, including OsMOT1;1 (molybdenum transporter) and OsACA9 (calcium ATPase homolog), associated with element accumulation.

Conclusions:

  • Genetic analysis in a MAGIC population effectively identified QTLs and candidate genes for element accumulation in rice.
  • Haplotype information aids in predicting genes like OsMOT1;1 and OsACA9, contributing to understanding element homeostasis.
  • Findings provide valuable genetic resources for breeding rice with improved nutritional value and optimized elemental uptake.