Computational genomics_
Structural variation at population scale.
I build breed-specific pangenome graphs, genotype the structural variants inside them across tens of thousands of animals, and test which ones actually move a trait. In practical terms: finding the genomic differences that change milk yield, fertility and growth — at the scale breeding programmes actually operate.
Selected numbers from published work_
assemblies in H20D
genotyped
largest SV-GWAS
mapped
papers
consortia
Raw counts from the published work below — every number traces to a paper.
What I do_
Pangenome graph construction
One graph per breed, built from phased assemblies, good enough to genotype the whole population — and the harder question of how many haplotypes, from which individuals, are enough.
Population-scale genotyping
From a graph to fifty thousand animals: graph-based genotyping on short-read cohorts, then imputation onto the reference populations where the phenotypes already exist.
Trait mapping
Which structural variants actually move a trait: association testing and fine-mapping on SVs rather than SNPs, with the enrichment and multiple-testing questions that come with a different variant class.
What I run_
The working stack, named rather than described. If a tool is on this list I have run it on real data and know where it breaks; the tool index says where.
- Assembly
- Graph
- Genotyping
- Variants & QC
- Statistics
- Workflow
Selected work_
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01 / 14Pangenome-based structural variant imputation enables large-scale genotype–phenotype studies in dairy cattleNature Communications · 2026First author
Genotyped 93,059 structural variants in 1,571 cattle from the H20D pangenome, built the HolPIP imputation panel, imputed 86.7% of them into 50,299 bulls at Beagle R² ≥ 0.8, and ran GWAS on 43 complex traits — 1,225 SV–trait associations and 32 fine-mapped candidates, including a 75 bp ANKRD11 deletion linked to stature.
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02 / 14Phased-assembly-driven pangenome graphs for structural variant genotyping and complex trait mapping in dairy cattleNature Communications · 2026First author
H20D — a Holstein breed-specific pangenome graph from 40 phased haploid assemblies of 20 cows. It outperforms assembly- and read-based long-read callers, finds over 10,000 additional SVs per sample versus short-read approaches, and beats graphs built across breeds or from fewer or unphased assemblies, particularly in complex regions.
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03 / 14Mapping and functional characterization of structural variation in 1060 pig genomesGenome Biology · 2024First author
An SV catalogue across 1,060 pigs from 101 breeds covering 9.6% of the genome — 42,487 deletions, 37,913 mobile element insertions, 3,308 duplications and 1,664 inversions — with functional characterisation against expression and complex traits.
Where the work has been done_
- University of MarylandDept. of Animal & Avian Sciences
- USDA-ARSAnimal Genomics & Improvement Lab, Beltsville
- FarmGTExConsortium member
- Ruminant T2TConsortium member
- NRSP-8Animal Breeding RCN, lead writer
Collaborate_
Have a cohort, a graph, or a trait that does not fit the papers?
Write to me. A graph that will not build, genotypes that look wrong, an imputation R² you do not trust — I am glad to look, and there is no fee for any of it. Where it turns into real analysis work, co-authorship or an acknowledgement is the usual arrangement.
Writing_
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Tool index · Reviewed September 2026
A working index of structural variation and pangenome tools
Which tools are still maintained in 2026, which have quietly stopped, where each one fails, and five places the field moved while a lot of pipelines stayed put — including a benchmark that many papers are still validating against after it was deprecated.