Evidence map›Paper›PMID 38456017›Full record

ArticleFrontiers in genetics2024

Linkage mapping and genomic prediction of grain quality traits in tropical maize (

Noel Ndlovu, Rajashekar M Kachapur, Yoseph Beyene, Biswanath Das, Veronica Ogugo, Dan Makumbi, Charles Spillane, Peter C McKeown, Boddupalli M Prasanna, Manje Gowda

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Article in Frontiers in genetics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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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

10 citing papers in PubMed.

  1. Article
  2. Meta-QTLs and candidate genes for kernel protein content in maize.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2026
    Article
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4 · The record

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5 · Who and what money

Authors and funding

10 authors.

Noel Ndlovu *Agriculture and Bioeconomy Research Centre, Ryan Institute, University of Galway, Galway, Ireland.
Rajashekar M Kachapur *International Maize and Wheat Improvement Center (CIMMYT), Nairobi, Kenya.
Yoseph BeyeneInternational Maize and Wheat Improvement Center (CIMMYT), Nairobi, Kenya.
Biswanath DasInternational Maize and Wheat Improvement Center (CIMMYT), Nairobi, Kenya.
Veronica OgugoInternational Maize and Wheat Improvement Center (CIMMYT), Nairobi, Kenya.
Dan MakumbiInternational Maize and Wheat Improvement Center (CIMMYT), Nairobi, Kenya.
Charles SpillaneAgriculture and Bioeconomy Research Centre, Ryan Institute, University of Galway, Galway, Ireland.
Peter C McKeownAgriculture and Bioeconomy Research Centre, Ryan Institute, University of Galway, Galway, Ireland.
Boddupalli M PrasannaInternational Maize and Wheat Improvement Center (CIMMYT), Nairobi, Kenya.
Manje GowdaInternational Maize and Wheat Improvement Center (CIMMYT), Nairobi, Kenya.

Funding

Gates Foundation INV-003439
6 · The paper itself

Abstract

The suboptimal productivity of maize systems in sub-Saharan Africa (SSA) is a pressing issue, with far-reaching implications for food security, nutrition, and livelihood sustainability within the affected smallholder farming communities. Dissecting the genetic basis of grain protein, starch and oil content can increase our understanding of the governing genetic systems, improve the efficacy of future breeding schemes and optimize the end-use quality of tropical maize. Here, four bi-parental maize populations were evaluated in field trials in Kenya and genotyped with mid-density single nucleotide polymorphism (SNP) markers. Genotypic (G), environmental (E) and G×E variations were found to be significant for all grain quality traits. Broad sense heritabilities exhibited substantial variation (0.18-0.68). Linkage mapping identified multiple quantitative trait loci (QTLs) for the studied grain quality traits: 13, 7, 33, 8 and 2 QTLs for oil content, protein content, starch content, grain texture and kernel weight, respectively. The co-localization of QTLs identified in our research suggests the presence of shared genetic factors or pleiotropic effects, implying that specific genomic regions influence the expression of multiple grain quality traits simultaneously. Genomic prediction accuracies were moderate to high for the studied traits. Our findings highlight the polygenic nature of grain quality traits and demonstrate the potential of genomic selection to enhance genetic gains in maize breeding. Furthermore, the identified genomic regions and single nucleotide polymorphism markers can serve as the groundwork for investigating candidate genes that regulate grain quality traits in tropical maize. This, in turn, can facilitate the implementation of marker-assisted selection (MAS) in breeding programs focused on improving grain nutrient levels.

Indexed as

genomic predictiongrain quality traitsquantitative trait locisub-Saharan Africatropical maize

Identifiers

PMID38456017
PMCPMC10918846

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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.