Comparative genomics identifies maize lethal necrosis resistance candidates

Comparative genomics has identified a set of candidate genes that may provide new genetic resources for combating maize lethal necrosis, a disease caused by synergistic infection with maize chlorotic mottle virus and a potyvirus, usually sugarcane mosaic virus. Researchers compared four tropical maize lines with contrasting responses to the disease and examined sequence variation within five previously mapped quantitative trait loci, or QTL. The analysis narrowed broad genetic regions to testable genes and mutations, but did not establish any candidate as a functional cause of resistance or susceptibility.

Maize lethal necrosis, commonly abbreviated MLN, is a significant threat to maize production in sub-Saharan Africa. The disease does not arise from infection by a single pathogen: it results from synergy between maize chlorotic mottle virus, a machlomovirus, and one of several potyviruses. Sugarcane mosaic virus was the principal potyvirus partner identified in a survey of MLN-associated viruses in Kenya.

Most maize hybrids deployed in sub-Saharan Africa have been described as susceptible, and MLN can affect plants at multiple developmental stages. Host resistance therefore remains a feasible approach to disease management, but rapidly evolving viruses and a limited set of deployed resistance sources create continuing demand for additional resistance genes. For the analysis, the researchers used the moderately resistant line CML543 as the reference for pairwise whole-genome alignments with CKL05004, CKL05022, CML536 and KS23-6.

The first three lines are adapted to sub-Saharan Africa and used in CIMMYT hybrid-breeding programs, whereas KS23-6 is not adapted to the region and is highly resistant. CML536 was the most susceptible of the selected materials, while KS23-6 has a chromosome 6 resistance locus associated with maize chlorotic mottle virus. CKL05004 shares a close ancestral relationship with CML543, providing an opportunity to determine whether the alignment results reflected known pedigree relationships.

Differences were classified as single-nucleotide polymorphisms, insertions and deletions smaller than 50 base pairs, and structural variants larger than 50 base pairs. CKL05004 had the fewest differences from CML543, consistent with their close relatedness. KS23-6 showed the greatest overall sequence divergence, while CML536 had the largest numbers of insertions and deletions and structural variants among the African-adapted lines.

The KS23-6 comparison also revealed a highly conserved segment toward the end of chromosome 10. The researchers did not establish the biological significance of that segment, but noted that other chromosome 10 QTL have been associated with resistance to several maize viruses. Attention then shifted to marker-defined MLN QTL intervals on chromosomes 1, 3, 5, 6 and 9.

The regions were selected according to the strength of the reported QTL signal and whether CML543 had appeared in the relevant mapping population. They were not fine-mapped in this study, so their boundaries could remain broad or exclude more precisely localized causal regions identified later. Every gene within the intervals was examined, and genes with known or predicted functions in viral replication, movement, translation, RNA silencing, vesicle trafficking or defense signaling were prioritized.

The resulting candidates included RNA helicases, RNA-binding proteins, WRKY transcription factors, methyltransferases, translation-initiation factors and SNARE-associated Golgi proteins. A 4.9-megabase region on chromosome 3 contained another RNA helicase, an S-adenosyl-L-methionine-dependent methyltransferase and a remorin-related protein. Three intervals on chromosome 5 yielded a replication protein A subunit, a WRKY transcription factor, methyltransferases, two ADP-ribosylation factors, a Tobamovirus multiplication protein 3 ortholog and a SNARE-associated Golgi protein.

Candidates on chromosome 6 included several methyltransferases, a nucleic acid-binding protein, a glutathione S-transferase, an RNA-binding protein and a syntaxin or t-SNARE family member. Variation was generally lower in CKL05004 than in the more genetically distant lines, while CML536 showed conspicuous differences in several virus-related genes. The researchers also filtered the candidates according to predicted mutation impact, distinguishing changes more likely to affect protein coding or expression from those more likely to be synonymous, in noncoding regions or otherwise less consequential.

Four genes showed differential expression in RNA-sequencing data generated in earlier work: the plasmodesmata callose-binding protein PDLP5, the methyltransferase Zm00001d036277, the WRKY transcription factor Zm00001d017444 and a glutathione S-transferase. The current study analyzed those previously generated data rather than conducting new infection experiments. PDLP5, located within the chromosome 9 interval, was predominantly downregulated in susceptible CML536 compared with the other lines.

It was also lower in moderately resistant CML543 than in highly resistant KS23-6, but higher in CML543 than in CML536. PDLP5 regulates plasmodesmata, the channels connecting adjacent plant cells, by positively regulating callose deposition; increased callose narrows these channels and can restrict pathogen spread. Potyvirus movement proteins can promote the opposite effect.

The expression pattern was therefore consistent with a possible role for PDLP5 in susceptibility, especially during sugarcane mosaic virus infection, although the study did not directly test virus movement. The methyltransferase Zm00001d036277 showed a similar pattern, with lower expression in CML536 and higher expression in CML543. Potyviral proteins can interfere with the methionine cycle and host RNA-silencing machinery, and previous work cited by the researchers found that the potyvirus helper-component protein HC-Pro can reduce methyltransferase activity and inhibit the HEN1 methyltransferase responsible for stabilizing small interfering RNAs.

Based on this evidence, the authors proposed that reduced expression of Zm00001d036277 in CML536 might inhibit host RNA-silencing mechanisms and facilitate infection. That mechanism was not directly tested, and the expression association does not establish causality. The WRKY transcription factor Zm00001d017444 was upregulated in both CML543 and CML536 but downregulated in KS23-6, while the glutathione S-transferase Zm00001d038192 was mainly downregulated in susceptible genotypes.

The broader candidate set also included genes that may promote infection under particular viral conditions. TOM3-related proteins from chromosomes 5 and 9 varied strongly in CML536 but not CKL05004, while eIF(iso)4E and eIF2 alpha were included because translation factors can be exploited by plant viruses. RNA helicases appeared repeatedly across the intervals and can either support viral replication or contribute to antiviral immunity, depending on the host factor involved.

RRM-containing proteins could affect viral RNA movement, replication or translation, while SNARE proteins may participate in endomembrane trafficking and formation of viral replication complexes. The recurrence of related functional classes across several chromosomes suggests that MLN responses may involve multiple interacting pathways, but the study did not determine which variants or genes have the largest effects in planta. The findings are best treated as a prioritized set of hypotheses.

The researchers did not fine-map the QTL, directly manipulate the candidate genes or demonstrate that a particular mutation changed virus replication, cell-to-cell movement or whole-plant disease resistance. The chromosome 6 interval used here lay upstream of the more finely mapped qMLNS1 region containing a reported causal peptidase variant, illustrating how marker-defined boundaries can omit causal sequence. Some candidates may confer only minor or partial effects, and neither sequence associations nor differential expression establish that resistance is caused by the observed variations.

The next steps proposed by the authors are fine-mapping, interval analysis, map-based cloning and functional tests using gene editing, overexpression, complementation or other targeted assays. Even with these limitations, the comparison connects broad QTL discoveries with specific genes and testable variants, providing a foundation for diversifying maize resistance to the two-virus combination that causes MLN.

Subject of Research: Comparative genomics of maize lethal necrosis QTL and candidate virus-response genes

Article Title: A comparative genomics approach to characterize variation within maize lethal necrosis-associated QTL to identify new sources of resistance

Article References: Murithi, A., Panangipalli, G., Fengler, K., Llaca, V., Lübberstedt, T., Dhugga, K. S., & Jung, M. (2026). A comparative genomics approach to characterize variation within maize lethal necrosis-associated QTL to identify new sources of resistance. Frontiers in Genetics, 17, Article 1955035. https://doi.org/10.3389/fgene.2026.1955035

Image Credits: AI Generated

DOI: 10.3389/fgene.2026.1955035

Keywords: maize lethal necrosis, maize, comparative genomics, structural variation, maize chlorotic mottle virus, sugarcane mosaic virus, QTL mapping, plant virus resistance, RNA silencing, maize breeding, comparative, genomics