The study, published in Plant Cell Reports by Ninh Hai Ho, Marcus Linde and Thomas Debener of Leibniz University Hannover, focused on transient expression, the short-lived production of a protein from DNA that has been delivered into cells but not stably integrated into the genome. Transient assays are prized in plant research because they allow scientists to test promoters, reporters and candidate genes within days rather than the many months required to regenerate a fully transgenic plant. In roses, however, even this shortcut is complicated by the fact that different varieties respond very differently to infiltration, and until now nobody had examined that variation at the level of the whole genome. Stable transformation of rose remains laborious, genotype-dependent and unavailable as a routine tool for most cultivars, making fast transient systems especially valuable for a species whose genome harbors genes controlling flower colour, scent, senescence, stress responses and plant architecture.

To dissect the genetic basis of this variation, the researchers assembled an association panel of 96 rose genotypes, 87 of them tetraploid, alongside eight triploid and one diploid variety, grown under semi-controlled greenhouse conditions at the Federal Plant Variety Office in Hannover. From flowers at the initial and full bloom stages, the developmental windows previously shown to be most amenable to petal agroinfiltration, the team harvested petals from the middle of each flower and infiltrated them from the abaxial side using a needleless syringe. The bacterial strain carried a T-DNA containing an intron-containing green fluorescent protein reporter driven by the Arabidopsis ubiquitin 10 promoter, a construct designed so that any detectable fluorescence would reflect successful delivery, nuclear import and expression of the transgene inside rose cells. The petals were then incubated and scored for fluorescence at three and five days after infiltration.

The phenotypic results were striking. Using a five-class ordinal scale ranging from no detectable expression to very strong expression, the researchers found that mean scores at five days post-infiltration ranged from zero to 3.98 across the panel, an almost complete sweep of the possible range. At three days, 33 of the 96 genotypes showed no GFP signal at all, but by five days only 13 remained dark, and the number of genotypes showing strong or very strong expression increased over time. Statistical testing confirmed that genotypic effects were highly significant at both time points, and the scores from the two time points correlated strongly, with a Pearson coefficient of 0.90. Cultivars such as Sebastian Kneipp, Friesia and Comtessa AL emerged as the most permissive genotypes, with Sebastian Kneipp reaching a mean score of 3.98 at the five-day endpoint. These varieties, the authors suggest, are immediate candidates for researchers seeking reliable petal-based transient assays in rose.

With the phenotype quantified, the team turned to genome-wide association analysis, using genotyping data from the WagRhSNP 68K Axiom SNP array. After quality filtering, 37,161 high-quality single-nucleotide polymorphisms remained for analysis. The researchers employed GWASpoly, software designed for autopolyploid species that tests different allele-dosage models, and controlled for population structure and relatedness with a kinship matrix and principal components. The analysis revealed a major association on chromosome 2, in a region spanning roughly four million base pairs from 69 to 73 megabase pairs. The strongest marker, at 70.13 megabase pairs, reached a significance of minus log10 P equals 7.85 under a simplex dominance model, well beyond the genome-wide threshold of 5.54. A second peak appeared on so-called chromosome 0 contigs, sequences not yet assigned to any of the seven rose pseudochromosomes, but follow-up sequence comparisons indicated that these unanchored fragments most likely belong to the same chromosome 2 region.

Within the associated interval, the researchers identified a collection of candidate genes whose annotated functions read like a checklist of the host processes known to matter during Agrobacterium-mediated transformation. Among them are an ABC transporter B family member 19 homologue involved in auxin transport, a Cullin 3 homologue representing the ubiquitin-mediated protein degradation machinery, DExH-box RNA helicases and an RNA-binding protein that could influence the processing of delivered transcripts, a hypersensitive-induced response protein 1-like membrane protein tied to defence signalling, monodehydroascorbate reductase 4, and several nuclear pore complex protein GP210-like sequences. Each of these annotations is biologically plausible. The ubiquitin-proteasome system has been implicated in the turnover of T-complex-associated proteins during bacterial DNA transfer, nuclear import is an essential step between T-DNA delivery and reporter expression, and plant immune signalling is well known to restrict transformation efficiency, as illustrated by the MKK4/5-MPK3/6 cascade that modulates Agrobacterium transformation in Arabidopsis.

The allele-dosage patterns at representative SNPs added further weight to the association. For two markers near 70.13 to 70.16 megabase pairs, genotypes carrying a low allele dosage showed substantially higher median GFP scores than other dosage classes, while for two other markers the opposite homozygous or quadruplex dose class presented the highest expression. Among cultivars in the high-expression dosage classes for two of these SNPs, 25 of 46, or 54.3 percent, reached GFP scores of two or better. The authors are careful, however, to frame the finding appropriately. With only 96 genotypes in the panel, mapping resolution is limited, and local linkage disequilibrium in the panel decays over megabase-scale distances. The chromosome 2 interval should therefore be treated as a high-priority candidate region containing multiple potential host factors rather than as evidence for a single causal gene, and larger panels combined with candidate-gene sequencing will be needed to pinpoint the responsible variants.

An intriguing wrinkle emerged when the team compared their GFP expression data with fragrance scores previously collected from the same association panel. The chromosome 2 region overlaps with marker clusters previously linked to fragrance-related variation, yet direct comparison revealed only a weak positive correlation of 0.27, explaining less than eight percent of the phenotypic variance. This suggests that the two traits are likely governed by different but linked loci within the same broad genomic region rather than by a single gene with pleiotropic effects, a distinction that future fine-mapping work will need to resolve.

The authors also emphasize what their phenotype does and does not measure. The score reflects visible transient GFP expression, not bacterial migration, T-DNA copy number or stable transformation efficiency. Low expression could stem from many causes, including reduced bacterial entry, impaired T-DNA transfer, rapid silencing, tissue necrosis, cuticle properties or defence activation, while high transient expression does not guarantee efficient regeneration of stable transgenic lines. Future work, they suggest, should incorporate quantitative image analysis of fluorescence, histological assessment of petal tissue and direct measurement of bacterial load, alongside sequencing and functional testing of the strongest candidate genes in contrasting genotypes.

Even with those caveats, the study delivers practical value immediately. The permissive cultivars identified in the screen give rose researchers a shortlist of genotypes for rapid petal-based gene function tests, potentially accelerating work on petal abscission, dehydration tolerance and pigmentation before any stable transformation is attempted. More broadly, the finding that transformation responsiveness behaves as a genetically tractable trait, echoing earlier quantitative trait locus work in Brassica oleracea and a recent GWAS of hairy root formation in rose, opens a new frontier in understanding the host side of Agrobacterium-mediated gene transfer. If the chromosome 2 interval can be narrowed and its candidate genes validated, the humble rose may yet teach biotechnologists a great deal about why some cells say yes to foreign DNA and others say no.

Subject of Research: Genetic control of Agrobacterium-mediated transient GFP expression in rose petals

Article Title: A chromosome 2 locus controls transient Agrobacterium-mediated GFP expression in rose petals

Article References: A chromosome 2 locus controls transient Agrobacterium-mediated GFP expression in rose petals. (n.d.). https://doi.org/10.1007/s00299-026-03961-z

Image Credits: AI Generated

DOI: 10.1007/s00299-026-03961-z

Keywords: rose, Agrobacterium tumefaciens, transient expression, GFP, genome-wide association study, chromosome 2, petal agroinfiltration, tetraploid rose, candidate genes, plant transformation, functional genomics, host susceptibility

Unlike influenza A, influenza B virus lacks a broad animal reservoir and, with it, the pandemic potential that makes influenza A a constant global security concern. But the absence of pandemic risk has never equated to clinical irrelevance. Influenza B virus drives substantial morbidity in seasonal epidemics, and its two historically circulating lineages, B/Victoria and B/Yamagata, have followed strikingly different trajectories in recent years. Surveillance has documented no confirmed naturally circulating B/Yamagata-lineage viruses since March 2020, a development widely linked to the intense non-pharmaceutical interventions of the COVID-19 pandemic era. Current influenza B activity is now overwhelmingly attributable to B/Victoria-lineage viruses, a shift with real consequences for vaccine composition and the interpretation of vaccine effectiveness studies.

The central premise of the review is that the host genome may help explain a persistent puzzle: why individuals exposed to the same virus, and receiving the same vaccine, experience markedly different outcomes. Variation in genes governing antigen presentation, innate viral sensing, interferon signaling, and host dependency or restriction factors could plausibly generate heterogeneity in susceptibility, disease severity, cross-lineage immunity, and responsiveness to immunization. This framework draws on decades of immunogenetic research in influenza A and in broader antiviral biology, but the authors stress a crucial caveat: much of what has been proposed for influenza B rests on inference rather than on direct, influenza B virus-specific human data.

At the heart of the immunogenetic hypothesis lies the human leukocyte antigen system, the protein complex responsible for presenting viral peptide fragments to T cells. Differences in HLA alleles can alter which viral epitopes are displayed, how strongly T cells respond, and consequently how efficiently an infected or vaccinated individual clears virus or mounts protective memory. For influenza A, associations between specific HLA variants and outcomes such as infection risk, severity, and antibody titers after vaccination have been reported across multiple populations. Extending these findings to influenza B is not straightforward, however, because the two virus types differ in their evolutionary dynamics, transmission patterns, and the antigenic landscape they present to the immune system. Epitope repertoires are not interchangeable, and a genetic variant that enhances clearance of one influenza type may have little or no measurable effect on the other.

Beyond antigen presentation, the review considers the innate immune machinery that first detects invading influenza viruses. Pattern recognition receptors such as the toll-like receptors and RIG-I-like receptors sense viral RNA and trigger signaling cascades that culminate in interferon production. Genetic polymorphisms in these sensors and in the downstream interferon pathway can modulate the vigor of the early antiviral response, potentially determining whether an infection is contained quickly or gains a foothold. Similarly, host dependency factors that the virus requires for entry, replication, and assembly, along with restriction factors that actively inhibit viral replication, represent additional layers where inherited variation could shape susceptibility. Each of these domains offers a plausible mechanistic route by which host genotype could influence influenza B outcomes, yet the authors find that direct evidence in the influenza B context remains sparse and fragmentary.

When it comes to vaccine response, the review is similarly measured. The best-supported determinants of influenza vaccine performance, the authors conclude, are not genetic at all. Antigenic match between vaccine strains and circulating viruses, the continuous process of antigenic drift that erodes that match over time, the age of the vaccinee, prior exposure history, and baseline immunity stand out as the factors with the strongest evidentiary grounding. These non-genetic determinants have been repeatedly validated across seasons and populations, and they explain a considerable portion of the year-to-year variability in vaccine effectiveness. Genetic predictors specific to influenza B, by contrast, remain incompletely defined, and no validated host-genetic biomarker currently exists to guide vaccination decisions for this virus.

This asymmetry between well-established extrinsic factors and poorly characterized intrinsic ones is not merely an academic gap. Predictive models of influenza B immune control and vaccine performance are limited by the absence of genotype-linked outcome data. Without large, well-phenotyped cohorts in which host genotype, immune phenotyping, and lineage-resolved virologic outcomes are collected together, the field cannot distinguish genuine genetic effects from confounding by age, prior exposure, or antigenic distance. The authors argue that such integrated studies represent the most important priority for future research, and they outline a research agenda built around linking these data streams in a single analytical framework.

The disappearance of the B/Yamagata lineage adds an unusual wrinkle to this agenda. With no naturally circulating Yamagata viruses detected for years, vaccine components targeting that lineage have become biologically obsolete, and regulatory and advisory bodies have been reconsidering the composition of seasonal vaccines, including the transition from quadrivalent to trivalent formulations. For immunogenetic studies, the loss of a circulating lineage complicates the interpretation of historical cross-lineage immunity data and underscores the need for lineage-resolved outcome measures in future cohorts. Any genetic association study conducted today will, in practice, be measuring responses against B/Victoria viruses, and generalizing those findings to influenza B as a whole carries inherent uncertainty.

Population-specific variation presents another challenge. Immunogenetic associations identified in one ancestry or geographic setting frequently fail to replicate elsewhere, reflecting both genuine differences in allele frequencies and differences in study design, exposure patterns, and co-circulating pathogens. The international composition of the review team, spanning institutions in China, Pakistan, and Uzbekistan, reflects a growing recognition that influenza B research must extend beyond the settings where it has traditionally been studied. Building the evidence base for immunogenetic determinants will require multi-center collaborations with standardized genotyping platforms, harmonized immune phenotyping protocols, and consistent definitions of susceptibility, severity, and vaccine response.

The review, which received support from the Guangdong Basic and Applied Basic Research Foundation and the Dongguan Science and Technology of Social Development Program, ultimately delivers a message of disciplined optimism. The biological logic connecting host genetic variation to influenza B outcomes is sound, and the methodological tools needed to test it, from affordable genome sequencing to sophisticated immune profiling, are now widely available. What is missing is the concerted, influenza B-specific data collection that would convert plausible mechanisms into clinically actionable knowledge. Until that work is done, antigenic match, age, and exposure history will remain the most reliable predictors of how influenza B behaves in populations, while the genome’s contribution waits to be quantified.

Subject of Research: Immunogenetic determinants of influenza B virus susceptibility and vaccine response

Article Title: Immunogenetic determinants of influenza B virus susceptibility and vaccine response: current evidence, gaps, and future directions

Article References: Din, G. U., Khan, H., Tariq, Z., Zhao, J., Khan, A., Eshboev, F., Xu, G., Hu, Y., & Huang, K. (2026). Immunogenetic determinants of influenza B virus susceptibility and vaccine response: current evidence, gaps, and future directions. Virology Journal. https://doi.org/10.1186/s12985-026-03292-1

Image Credits: AI Generated

DOI: 10.1186/s12985-026-03292-1

Keywords: influenza B virus, immunogenetics, host susceptibility, vaccine response, immune heterogeneity, antigenic drift, HLA, interferon, B/Victoria lineage, B/Yamagata lineage, Immunogenetic, determinants