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Genetics, Genomics and Breeding for Resistance to Northern Corn Leaf Blight in Maize: A Critical Synthesis of Recent Advances and Future Priorities

Jul 2026 · Journal of Advances in Biology & Biotechnology · Vol 29, pp. 905-927 · 0 citations

TL;DR

Future progress requires coordinated host pangenomics, pathogen surveillance, standardised component-trait phenotyping, cross-environment causal validation and breeding strategies that integrate major genes with quantitative background resistance rather than substituting one for the other.

Abstract

Northern corn leaf blight is a recurrent constraint on maize production across temperate, subtropical and tropical environments. Resistance breeding has progressed from phenotypic selection and race-specific Ht genes to high-density mapping, genomic prediction, functional genomics and, recently, targeted genome editing. Yet the expanding catalogue of loci has not produced a correspondingly simple route to durable resistance. This critical narrative review evaluates how genetic architecture, pathogen variation, phenotyping quality and breeding design interact to determine translational success. Literature published from 1 January 2000 to 24 May 2026 was considered, with earlier foundational studies retained where necessary. Evidence was selected from accessible scholarly indexes and verified journal records, then synthesised by resistance mechanism, mapping resolution, functional validation and breeding readiness. The strongest mechanistic evidence distinguishes an intracellular nucleotide-binding leucine-rich repeat receptor encoded by Ht1 from allelic wall-associated kinase variants underlying Htn1, Ht2 and Ht3. This reinterpretation cautions against treating historically named loci as independent stacking targets. Quantitative resistance remains indispensable because it is distributed across many small- to moderate-effect loci and is often less vulnerable to single virulence changes, but most reported quantitative trait loci and marker–trait associations show restricted portability across populations and environments. Genomic selection can capture dispersed effects more effectively than sparse marker-assisted selection, although prediction accuracy varies markedly with training-population size, relatedness, marker density and environmental connectedness. Transcriptomic and proteomic studies consistently implicate cell-wall reinforcement, phenylpropanoid metabolism, redox regulation and immune signalling, but candidate-gene lists frequently exceed the available causal evidence. Genome-edited combinations of native resistance alleles provide a compelling proof of concept, while durability across broader pathogen populations, genetic backgrounds and production environments remains unresolved. Future progress requires coordinated host pangenomics, pathogen surveillance, standardised component-trait phenotyping, cross-environment causal validation and breeding strategies that integrate major genes with quantitative background resistance rather than substituting one for the other.

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