Genome assembly & annotation
De novo assembly of non-model genomes to chromosome scale, with completeness assessment and gene and repeat annotation.
Research Area
Agriculture & Evolutionary Biology
From a wild genome no one has assembled to a breeding program spanning thousands of individuals—non-model biology brings its own hard problems. We bring the computational depth to match: genome assembly, population genomics, phylogenomics, selection scans, and genomic selection, for research.
Any organism · non-model
WGS · RAD-seq / GBS
Assembly · popgen · breeding
Research predictions · no guarantees
Illustrative sample output
collinear
inverted
translocated
Overview
Genomics for the whole tree of life, not just the model organisms
Most genomics tooling assumes a polished reference genome and a human-shaped problem. Agriculture and evolutionary biology rarely offer either. Genomes are often large, repetitive, and polyploid; references may not exist; sampling spans hundreds of individuals across populations and environments; and the questions—diversity, adaptation, ancestry, breeding value—need population-scale and comparative methods rather than single-sample pipelines.
We work across that whole space. From de novo assembly and annotation of non-model genomes to population genomics, phylogenomics, selection scans, genomic selection, and conservation genetics, we apply established, peer-reviewed methods at population scale—and return results documented for reproducibility. Where we estimate breeding values or selection signals, we are clear that these are research predictions: they need validation, and field performance also depends on environment and management.
Applications
What we analyse in agriculture & evolution
The computational analyses that span assembly to breeding—from non-model genomes and population structure to selection and comparative genomics.
Population genomics & diversity
Diversity and differentiation statistics, population structure, admixture, and effective-population-size estimation.
Phylogenomics & comparative
Orthology inference, gene and species trees, and comparative genomics across many taxa, including synteny.
Selection & adaptation
Genome scans for selection, environmental-association analysis, and molecular-evolution tests of adaptation.
Genomic selection & breeding
GWAS and genomic-selection models to estimate breeding values (GEBVs)—research predictions, not guaranteed outcomes.
Conservation genomics
Runs of homozygosity, inbreeding, and effective-population-size estimation to inform conservation research.
Pangenomics
Graph pangenome construction and structural-variation analysis to capture diversity a single reference misses.
Biodiversity & metabarcoding
eDNA and metabarcoding analysis for species identification and biodiversity assessment from environmental samples.
The Pipeline
A representative agri-genomics workflow
A transparent, organism-agnostic sequence from raw data to interpreted biology—each step suited to your species and question and documented for reproducibility.
Adapted to your study: reference vs. de novo, WGS vs. RAD/GBS, single population vs. many taxa, diversity vs. breeding. We confirm the plan with you before any compute begins.
Intake & QC
Raw reads are quality-checked—quality, adapters, contamination, and ploidy and genome-size estimation.
Tools: fastp · GenomeScope · MultiQC
Assembly / alignment & annotation
A genome is assembled and annotated, or reads aligned to a reference, with completeness assessed by BUSCO.
Tools: hifiasm · BWA-MEM2 · BRAKER
Variant calling & genotyping
Variants are called across individuals—including RAD-seq/GBS genotyping—then filtered for quality and missingness.
Tools: GATK · Stacks · bcftools
Population structure & diversity
Diversity, differentiation, structure, and admixture are estimated across populations and samples.
Tools: ANGSD · ADMIXTURE · PCA
Selection, phylogeny & breeding
Depending on the goal: selection scans, phylogenomic trees, or genomic-selection breeding-value models.
Tools: SweeD · IQ-TREE · rrBLUP
Comparative & functional context
Signals are placed in comparative and functional context—orthology, synteny, gene families, and enrichment.
Tools: OrthoFinder · CAFE · synteny
Integration & reporting
Results become structure plots, trees, synteny and selection figures, tables, and reproducible methods with every tool version.
Tools: ggplot2 · R · versioned manifest
Tools & Technologies
Established, peer-reviewed tools—matched to your data
We select from the field's standard toolkit rather than forcing every dataset through one pipeline. A representative set of what we work with:
Assembly & annotation
hifiasm
Flye
purge_dups
BUSCO
BRAKER
Variant & genotyping
GATK
Stacks
bcftools
VCFtools
Population genomics
ANGSD
PLINK
ADMIXTURE
PopLDdecay
GONE
Phylogenomics
OrthoFinder
IQ-TREE
ASTRAL
MAFFT
Selection & evolution
SweeD
BayPass
PAML
CAFE
Genomic selection & breeding
rrBLUP
BGLR
GAPIT
TASSEL
Pangenomics & SVs
PGGB
minigraph-cactus
vg
MUMmer
Visualization & databases
ggplot2
Ensembl Plants
Phytozome
OrthoDB
Key Databases
The genomics resources we draw on
Cross-species analysis is powered by reference genomes, ortholog sets, and biodiversity databases. We build on the community's authoritative, versioned resources.
- Ensembl Plants
- Reference plant genomes, gene models, and comparative data.
- Ensembl Metazoa
- Reference genomes and annotation across animal taxa.
- NCBI / GenBank
- The primary archive of sequences and assemblies.
- Phytozome
- Plant genomes with gene families and comparative tools.
- Gramene
- Comparative plant genomics for crops and models.
- OrthoDB
- Hierarchical catalog of orthologs across the tree of life.
- BUSCO lineages
- Near-universal single-copy orthologs for completeness.
- GBIF
- Global biodiversity occurrence records for context.
- BOLD
- Barcode of Life reference library for species ID.
Choosing an Approach
RAD-seq/GBS vs. WGS resequencing vs. de novo
Different strategies trade cost against completeness. A quick orientation; we will help you match it to your study.
| Dimension | RAD-seq / GBS | WGS resequencing | De novo assembly |
|---|---|---|---|
| Genome coverage | Reduced-representation | Whole genome, needs reference | Builds the reference |
| Cost / sample | Lowest—many samples | Moderate | Highest, per genome |
| Reference needed | Optional | Yes | No |
| Resolves SVs | No | Partially | Yes |
| Best suited to | Large population & breeding panels | Diversity & selection scans | New species & pangenomes |
What You Receive
A complete, documented deliverable
Not just a VCF dropped in a folder—a coherent picture of your organisms and populations, documented so it reproduces.
- Assembled, annotated genome with BUSCO completeness, where applicable
- Filtered variant set & genotype matrix across individuals
- Diversity, differentiation & population-structure results
- Selection-scan or phylogenomic results, per your question
- Estimated breeding values (GEBVs) with accuracy, where applicable
- Structure, tree, synteny & scan figures (publication-quality)
- Reproducible methods with every tool & reference version
Built for reproducibility, not just a result
Population-scale analysis follows documented best practices—ploidy and genome-size checks, careful variant filtering and relatedness control, assembly completeness assessed by BUSCO, and reference and database versions pinned—so a selection signal or a structure result is real signal, not a filtering artifact or reference bias. Where we estimate breeding values or predictive models, we are explicit that these are research predictions with a stated accuracy: they need independent validation, and real-world field or population outcomes also depend on environment, management, and factors outside the genome, so we make no guarantees.
The practical payoff: your methods section writes itself, a reviewer can re-run the analysis, and a result from today can be reproduced a year from now. We will also tell you honestly when a design or sample size won't support the conclusion you're after.
FAQ
Agriculture & evolutionary biology questions
What plant, animal, and evolutionary-biology teams most often ask before starting.
Any organism, model or non-model — plants, animals, crops, livestock, wild species. We handle whole-genome sequencing (short- and long-read), reduced-representation data (RAD-seq/GBS), resequencing panels, and RNA-seq, from raw reads or assemblies from your core or public repositories.
Yes. De novo assembly of non-model genomes is core to this work — we assemble from long or hybrid reads, scaffold to chromosome level, assess completeness with BUSCO, and annotate genes and repeats.
Yes. We compute diversity and differentiation statistics, infer population structure and admixture, estimate effective population size and inbreeding, and run selection and environmental-association scans.
Yes. We run GWAS and build genomic-selection models to estimate breeding values (GEBVs) for research and breeding programs. These are statistical predictions that need validation; real-world performance also depends on environment and management, so we make no guarantees of field outcomes.
Yes. We infer orthology, build gene and species trees (including coalescent methods), and run comparative and molecular-evolution analyses such as gene-family expansion and dN/dS.
Agriculture and evolutionary biology is a research area we support through our core services — chiefly Genomics & Variant Analysis, Biostatistics & Visualization, and Custom Pipelines & Software — applied to your organisms. This page shows how they come together.
Related
Services that power this work
Have genomes or populations to analyse?
Tell us your organism, data type, and question—we'll scope it honestly, including if a different design would serve you better.