Introduction: elevating microbiome profiling in the wheat phyllosphere
Understanding the complex microbial communities on wheat leaves is essential for disease management and crop health. Traditional ribosomal barcodes (16S/ITS) offer broad taxonomic coverage but often fall short in resolving closely related strains. A recently developed approach uses pangenome-informed, taxon-specific long-read amplicons to achieve species- and strain-level resolution in the wheat phyllosphere. This article summarizes how long-read, targeted amplicons were designed, validated, and applied to 480 field samples of eight European winter wheat varieties across five timepoints, revealing dynamic microbial landscapes within a single growing season.
From field sampling to mock communities: designing for diversity
The study began with field sampling of eight elite European winter wheat cultivars (Aubusson, Arobase, Lorenzo, CH Nara, Zinal, Simano, Forel, Titlis) across five dates, under natural infection by Zymoseptoria tritici. Leaves were collected at three canopy positions per plant, with two plants per plot, two blocks, and two replicates, totaling 480 leaves. Mock communities comprising Pseudomonas spp. and Z. tritici isolates were constructed to guide primer design and quantify detection limits. This rigorous setup ensured primers could recover diverse lineages while remaining specific to target organisms.
Pangenome-informed amplicon design: achieving higher resolution
Key to the approach is constructing pangenomes for target taxa (Pseudomonas and Z. tritici) from dozens of reference genomes to identify core, widely conserved regions with high nucleotide diversity across strains. For Pseudomonas, 1059 core regions were identified, and eight amplicon candidates (2.7–3.2 kb each) were shortlisted based on diversity metrics. For Z. tritici, two strong loci on chromosomes 9 and 13 emerged as top performers. Primer design leveraged multiple sequence alignments, consensus sequences, and degenerate bases to maximize retrieval of intraspecific diversity while maintaining specificity. This strategy yields taxon-specific long amplicons that outperform universal markers in resolving within-species diversity.
Validation and optimization
Candidate primer pairs were tested against a panel of lab strains and naturally infected leaves. An annealing temperature gradient and two touchdown PCR protocols identified robust conditions. Specificity was confirmed via Sanger sequencing, and amplicons were verified against reference genomes using BLAST/MAFFT alignments. Two primer pairs per organism were selected for downstream high-throughput amplicon sequencing, along with full-length 16S and ITS controls for comparison.
Robotic workflows and PacBio HiFi sequencing
Extraction and amplification benefited from automated, robotic handling to scale nearly 10,000 reactions in a single run. PacBio Sequel II HiFi sequencing produced high-quality long reads (>99% accuracy). Amplicons were size-selected (3 kb and ~1.5 kb for 16S/ITS), barcoded asymmetrically, and sequenced across two runs with different SMRT Link versions to accommodate mock and leaf samples. The approach balances high throughput with precise assembly of long amplicons, enabling deep resolution of microbial communities.
Data processing: from reads to ASVs and species
Circular consensus sequences (CCS) with Q20+ accuracy were demultiplexed by barcode, trimmed to remove primers, and analyzed with dada2 for amplicon sequence variant (ASV) inference. Taxonomy used: 16S (SILVA v138) and ITS (UNITE v8.3). For Pseudomonas and Z. tritici-specific amplicons, reads were assigned to reference amplicons, and ASVs were mapped to species or strain-level references with careful verification via BLAST against genome databases and pathogen-focused collections. This pipeline enables robust, cross-sample comparisons of community structure at high resolution.
Key findings: higher resolution, dynamic plant-microbe interactions
Across 480 leaf samples, Pseudomonas genera dominated the full-length 16S signal, with rpoD and an ABC transporter–coding amplicon revealing a richer, subspecies-level landscape (notably P. fluorescens and P. syringae groups). The Z. tritici amplicons uncovered substantial strain-level diversity within a single epidemic season, with two chromosome-specific loci outperforming ITS in resolving intra-species variation. When compared to 16S and ITS controls, the taxon-specific long amplicons yielded up to tenfold more ASVs, reducing ambiguity in species assignments and enabling tracking of genotype turnover across time and canopy height. Importantly, the approach captured spatial and temporal patterns, such as subspecies–height preferences and season-dependent abundance shifts for Pseudomonas lineages and stable yet diverse Z. tritici populations during epidemics.
Implications and broader potential
The pangenome-informed design of long, taxon-specific amplicons provides a scalable, cost-effective alternative to whole-genome metagenomics in settings with high host DNA and complex microbiomes. By enabling strain- and subspecies-level tracking in crops, this method supports targeted biocontrol development, disease forecasting, and precision agriculture strategies. The framework also generalizes to other taxa, including Rhizobia, Streptomyces, and Aspergillus fumigatus, offering a pathway to observe fine-scale diversity across ecosystems, from soils to human-associated microbiomes.
Looking ahead: challenges and opportunities
While powerful, the approach requires expert curation of representative genomes, careful primer optimization, and ongoing validation across diverse environments. Open-source pipelines for pangenome construction and amplicon design can democratize access, but users must balance design complexity with real-world throughput. As genome databases continue to expand, pangenome-informed long-read amplicons will likely become a mainstay for high-resolution microbiome studies in agriculture, environmental biology, and clinical research.
