Fungal Genomics · HiFi & ONT Long Reads

Through the repeats and beyond.

Fungal genomes defeat short-read assembly: repeat content up to 50%+ in some lineages, extreme GC content, dikaryotic/heterokaryotic states, and large families of duplicated genes. Long reads resolve what short reads collapse — and fungal-specific annotation (CAZymes, secondary metabolite clusters, effector repertoires) turns assemblies into biology.

Plan Your Project → Learn the Basics
HiFi + ONT
long-read assembly
Repeat-rich & GC-extreme
genomes handled
CAZyme & SM cluster
annotation
Dikaryon phasing
supported
About the Service

Fungal Genome Sequencing at Nucleome Informatics

Fungal genome sizes range from ~10 Mb (microsporidia, some yeasts) to well over 100 Mb (some filamentous fungi and rusts), with repeat content and GC extremes that vary enormously across the kingdom. Nucleome Informatics offers:

  • Chromosome-scale or contig-level assembly (per genome complexity and data) with QC (BUSCO fungi_odb10, QV/Merqury, N50)
  • Haplotype-resolved assemblies for dikaryotic/heterokaryotic isolates where data supports phasing
  • Gene prediction tuned for fungi (BRAKER/Funannotate/MAKER with fungal gene models)
  • Specialised annotation: CAZyme carbohydrate-active enzymes (dbCAN), secondary metabolite clusters (antiSMASH), effectors, transporters
  • Repeat landscape characterisation (RepeatModeler/RepeatMasker)
  • Comparative genomics: synteny, gene family expansion/contraction, phylogenomics

Why fungi need long reads

  • Repeats: transposable elements and tandem arrays break short-read assembly and hide gene duplications.
  • Dikaryons: two haploid nuclei in one mycelium (e.g. many basidiomycetes) need haplotype-aware assembly — long reads separate the haplotypes.
  • GC extremes: high/low GC regions are systematically biased in short-read workflows; long reads read through them.
Learning Path

From first principles to expert-level analysis

New here? Start with Foundations. Planning a study or reviewing results? Jump to Practitioner or Expert. Each level builds on the one before it, so you can read this page as a short course or dip in where you need to.

Start here if you are new to this service — six ideas that explain what it is and why it matters.

LEVEL 1

What is special about fungal genomes?

They range 10-fold in size, carry heavy repeat loads, and often exist as dikaryons (two haploid nuclei per cell). Short-read assemblers struggle with all three.

LEVEL 1

What is a dikaryon?

A fungal mycelium containing two genetically distinct haploid nuclei (common in basidiomycetes). Sequencing reads come from both genomes; assembly must separate them.

LEVEL 1

What are CAZymes?

Carbohydrate-active enzymes — the enzymes that break down or build carbohydrates. Their repertoire defines what a fungus can degrade (plant biomass, chitin, etc.) and is a headline output for industrial and plant-pathogen projects.

LEVEL 1

What are secondary metabolite clusters?

Groups of co-regulated genes (e.g. polyketide synthases, non-ribosomal peptide synthetases) that biosynthesise small molecules — antibiotics, mycotoxins, pigments. antiSMASH detects and classifies them.

LEVEL 1

Why not just use short reads?

For yeasts with small, repeat-poor genomes, short reads can suffice. For filamentous fungi, repeats and duplications make short-read assemblies fragmented and gene counts unreliable.

LEVEL 1

What samples do I send?

Purified DNA (high molecular weight for long reads) or a live culture. Single-spore isolation is recommended for heterokaryotic species unless the dikaryon itself is the target.

For scientists planning a project or reading a report: how each step works and how it can mislead.

LEVEL 2

Genome scoping

Genome size, repeat content, and ploidy are estimated (from k-mers and close relatives) before sequencing — data volumes are scoped accordingly.

LEVEL 2

Sequencing

HiFi libraries (Revio) for accuracy; ultra-long ONT (PromethION) for the largest repeats; optional Illumina for polish and population work.

LEVEL 2

Assembly and phasing

hifiasm/Verkko with HiFi (+UL-ONT where needed); dikaryons assembled into haplotype-resolved genomes; organellar genomes assembled and circularised.

LEVEL 2

Gene prediction and annotation

BRAKER/Funannotate/MAKER with RNA-seq evidence where available; functional annotation (eggNOG/InterPro); CAZymes (dbCAN), SM clusters (antiSMASH), effectors, and transporters reported as curated tables.

LEVEL 2

Repeat landscape

RepeatModeler/RepeatMasker characterise transposable elements and satellites — essential context for genome evolution and gene prediction.

LEVEL 2

Comparative genomics

Synteny plots, gene family expansion/contraction (orthogroup analysis), and phylogenomic placement across your isolate set.

For study design: the decisions that determine whether the data answers your question.

LEVEL 3

RNA-seq evidence for annotation

Fungal gene prediction improves dramatically with RNA-seq evidence from matched conditions (e.g. infection vs saprophytic growth). We can run the transcriptome alongside the genome.

LEVEL 3

Population and pan-genome studies

For species-level collections, short-read resequencing against a long-read reference plus pan-genome analysis captures accessory-gene dynamics (e.g. effector complements in plant pathogens).

LEVEL 3

Effector biology in plant pathology

Small, cysteine-rich secreted proteins are prioritised and annotated for plant-pathogen programmes; long-read assemblies recover effector gene families short reads miss.

LEVEL 3

Industrial and biotech programmes

CAZyme and SM-cluster inventories support enzyme-discovery and strain-development programmes; complete assemblies enable targeted engineering.

LEVEL 3

Taxonomy and description

Complete genomes, phylogenomics, and diagnostic markers support novel-species descriptions; NCBI submission formatting included.

LEVEL 3

Quality benchmarks

BUSCO fungi_odb10 completeness, QV ≥40 where achievable, Merqury consistency, and per-haplotype QC for dikaryons — reported honestly, including any unresolved regions.

Dikaryon
a mycelium with two genetically distinct haploid nuclei per cell.
CAZyme
carbohydrate-active enzyme.
antiSMASH
antibiotic and secondary metabolite analysis shell; SM cluster detection tool.
BRAKER/Funannotate/MAKER
genome annotation pipelines.
Effector
a secreted protein modulating host biology, central to plant pathology.
fungi_odb10
the BUSCO lineage dataset for fungal gene completeness.
The Science

How it works, in two figures

Fungal genome assembly with HiFi reads and haplotype-aware pipelines is established in the mycology genomics literature; CAZyme (dbCAN) and SM cluster (antiSMASH) annotation standards are community tools with active curation. See references below.

Figure 1 Repeat-driven fragmentation. schematic
Short-read assembly Long-read assembly Repeat-driven fragmentation Duplicated genes collapsed Dikaryon haplotypes merged Repeats and duplications resolved Haplotype-resolved dikaryons CAZyme & SM clusters annotated
Figure 1 | Repeat-driven fragmentation. (Illustrative schematic, not sample data.)
Figure 2 Workflow. schematic
Culture / HMW DNA HiFi / ONT sequencing Haplotype-aware assembly Fungal gene prediction CAZyme / antiSMASH annotation Comparative genomics
Figure 2 | Workflow. (Illustrative schematic, not sample data.)
Technology Highlights

Built for the questions you are asking

The platforms, pipelines and standards behind this service.

PacBio HiFi for fungal genomes

≥99.9% accurate reads at 15–20+ kb resolve repeat-rich filamentous fungal genomes and separate dikaryotic haplotypes.

Oxford Nanopore ultra-long reads

Multi-hundred-kb reads span the largest repeat arrays and rDNA clusters in large fungal genomes.

Fungal-tuned gene prediction

BRAKER, Funannotate, and MAKER with fungal gene models, RNA-seq evidence integration, and species-specific parameterisation.

CAZyme annotation (dbCAN)

Carbohydrate-active enzyme repertoires — the enzymatic inventory behind biomass degradation, pathogenesis, and industrial applications.

Secondary metabolite clusters (antiSMASH)

Biosynthetic gene cluster detection and classification — the basis of mycotoxin, antibiotic, and novel-metabolite discovery.

Dikaryon and polyploid handling

Haplotype-aware assembly and phasing for heterokaryotic and polyploid isolates, with per-haplotype QC. ---

Scope Note

What this service does and does not cover

Scope note. Assembly outcomes depend on genome architecture: extremely repeat-rich or polyploid genomes may retain unresolved regions, reported honestly per chromosome/scaffold. Dikaryon phasing quality depends on haplotype divergence and data depth. Gene prediction without RNA-seq evidence is model-based; we recommend transcriptome support for publication-grade annotation. Secondary metabolite cluster detection is bioinformatic prediction — cluster activity requires experimental validation.---
Why Nucleome

Service highlights

What you can expect from our team in Hyderabad.

Long-read first for fungi

HiFi and ultra-long ONT as the default, not the upgrade.

Fungal-specific annotation

CAZymes, SM clusters, effectors — not generic bacterial-style annotation.

Dikaryon-capable

Haplotype-resolved assemblies for heterokaryotic isolates.

RNA-seq integration

Transcriptome evidence for publication-grade gene models.

Plant-pathogen and industrial expertise

Effector repertoires and enzyme inventories for applied programmes.

NCBI-ready deliverables

Formatted assemblies and annotation for submission and publication. ---

Questions

Frequently asked, in plain language

From the basics to the finer points of design and interpretation.

basicWhy does my fungus need long reads?
Fungal genomes carry repeats and duplications that fragment short-read assemblies. Long reads assemble them correctly — often into chromosome-scale sequences.
basicWhat do you deliver?
Assembly with QC, gene prediction, functional annotation (including CAZymes and secondary metabolite clusters), and a written report.
basicHow much DNA is needed?
Micrograms of high-molecular-weight DNA for long reads; we provide extraction guidance or accept cultures.
intermediateCan you handle a dikaryotic isolate?
Yes — haplotype-aware assembly separates the two nuclei's genomes where divergence and data quality permit; per-haplotype QC is reported.
intermediateCan RNA-seq be added for better annotation?
Yes, and we recommend it — RNA-seq evidence substantially improves fungal gene models, especially for condition-specific genes.
intermediateDo you detect mycotoxin gene clusters?
antiSMASH detects and classifies biosynthetic gene clusters, including known mycotoxin clusters; cluster activity requires experimental confirmation.
advancedCan you support a pan-genome study across my fungal collection?
Yes — long-read reference assembly plus short-read resequencing of the collection, with pan-genome and accessory-gene analysis.
advancedCan you assemble polyploid fungal genomes?
Polyploidy increases assembly complexity; HiFi-based haplotype-aware strategies handle many cases. We scope feasibility honestly at design stage.
advancedCan you support novel species description?
Yes — complete genome, phylogenomics, diagnostic markers, and NCBI submission formatting.
advancedWhat QC standards apply?
BUSCO fungi_odb10, QV/Merqury, N50, and per-haplotype metrics for dikaryons — all reported, including unresolved regions.
References

Key literature & resources

Selected sources behind the methods and reference values on this page. Figures labelled "schematic" or "illustrative" are generated for this page, not client data.

  1. Cheng H, et al. Haplotype-resolved de novo assembly with phased assembly graphs (hifiasm). Nature Methods. 2021;18(2):170–175.
  2. Rautiainen M, et al. Telomere-to-telomere assembly of diploid chromosomes with Verkko. Nature Methods. 2023;20(10):1544–1552.
  3. Simão FA, et al. BUSCO: assessing genome assembly and annotation completeness. Bioinformatics. 2015;31(10):1670–1676.
  4. Brůna T, et al. BRAKER2/BRAKER3: unsupervised RNA-Seq-based genome annotation. Genome Biology. 2023;24:128. (Funannotate: Love MS, et al. GitHub documentation; MAKER: Cantarel BL, et al. Genome Research. 2008;18(1):188–196.)
  5. Zhang H, et al. dbCAN2/CAZy: automated carbohydrate-active enzyme annotation. Nucleic Acids Research. 2018;46(W1):W95–W101.
  6. Blin K, et al. antiSMASH 7.0: new and improved predictions for detection, regulation, and structure of biosynthetic gene clusters. Nucleic Acids Research. 2023;51(W1):W46–W50.
  7. Flynn JM, et al. RepeatModeler2 for automated genomic discovery of transposable element families. PNAS. 2020;117(17):9451–9457.
  8. Martin F, et al. — fungal genome complexity and dikaryon assembly context: see also the MycoCosm/JGI fungal comparative genomics resources (Grigoriev IV, et al. Nucleic Acids Research. 2014;42(D1):D622–D629).