Evidence map›Paper›PMID 35618915›Full record

ArticleTAG. Theoretical and applied genetics. Theoretische und angewandte Genetik2022

Genomic prediction of zinc-biofortification potential in rice gene bank accessions.

Mbolatantely Rakotondramanana, Ryokei Tanaka, Juan Pariasca-Tanaka, James Stangoulis, Cécile Grenier, Matthias Wissuwa

Abstract read
In one paragraph

Article in TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed
–field-weighted citation impact
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.

  1. Article
  2. Article
  3. Genome-wide association study reveals genetic loci for ten trace elements in foxtail millet (Setaria italica).TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2024
    Article
  4. Review
  5. Article
  6. Article
  7. Article
  8. Genomic prediction and QTL analysis for grain Zn content and yield inJournal of plant biochemistry and biotechnology · 2024
    Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Review
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

6 authors.

Mbolatantely RakotondramananaRice Research Department, The National Center for Applied Research on Rural Development (FOFIFA), 101, Antananarivo, Madagascar.
Ryokei TanakaDepartment of Agricultural and Environmental Biology, Graduate School of Agricultural and Life Sciences, The University of Tokyo, 1-1-1 Yayoi, Bunkyo, Tokyo, 113-8657, Japan.
Juan Pariasca-TanakaCrop, Livestock and Environment Division, Japan International Research Center for Agricultural Sciences (JIRCAS), 1-1 Ohwashi, Tsukuba, Ibaraki, 305-8686, Japan.
James StangoulisCollege of Science and Engineering, Flinders University, Bedford Park, SA, 5042, Australia.
Cécile GrenierCIRAD, INRAE, Institut Agro, UMR AGAP Institut, Univ Montpellier, 34398, Montpellier, France.
Matthias WissuwaCrop, Livestock and Environment Division, Japan International Research Center for Agricultural Sciences (JIRCAS), 1-1 Ohwashi, Tsukuba, Ibaraki, 305-8686, Japan. wissuwa@affrc.go.jp.ORCID http://orcid.org/0000-0003-3505-9398

Funding

Science and Technology Research Partnership for Sustainable Development JPMJSA1608
6 · The paper itself

Abstract

key messageA genomic prediction model successfully predicted grain Zn concentrations in 3000 gene bank accessions and this was verified experimentally with selected potential donors having high on-farm grain-Zn in Madagascar. Increasing zinc (Zn) concentrations in edible parts of food crops, an approach termed Zn-biofortification, is a global breeding objective to alleviate micro-nutrient malnutrition. In particular, infants in countries like Madagascar are at risk of Zn deficiency because their dominant food source, rice, contains insufficient Zn. Biofortified rice varieties with increased grain Zn concentrations would offer a solution and our objective is to explore the genotypic variation present among rice gene bank accessions and to possibly identify underlying genetic factors through genomic prediction and genome-wide association studies (GWAS). A training set of 253 rice accessions was grown at two field sites in Madagascar to determine grain Zn concentrations and grain yield. A multi-locus GWAS analysis identified eight loci. Among these, QTN_11.3 had the largest effect and a rare allele increased grain Zn concentrations by 15%. A genomic prediction model was developed from the above training set to predict Zn concentrations of 3000 sequenced rice accessions. Predicted concentrations ranged from 17.1 to 40.2 ppm with a prediction accuracy of 0.51. An independent confirmation with 61 gene bank seed samples provided high correlations (r = 0.74) between measured and predicted values. Accessions from the aus sub-species had the highest predicted grain Zn concentrations and these were confirmed in additional field experiments, with one potential donor having more than twice the grain Zn compared to a local check variety. We conclude utilizing donors from the aus sub-species and employing genomic selection during the breeding process is the most promising approach to raise grain Zn concentrations in rice.

Indexed as

BiofortificationOryzaEdible GrainGenetic Association StudiesGenomicsPlant BreedingZincZinc

Identifiers

PMID35618915
PMCPMC9271118

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.