GWAS
Holstein GWAS across 31 dairy traits
Open access · cc by · source: Europe PMC
Genome-wide SNP association in U.S. Holsteins links many loci to production, health, fertility, and type traits.
Study at a glance
- Design
- Computational / modelling — GWAS of ~46k SNPs against PTA traits in contemporary US Holsteins
- N
- N=1654 · 1,654 Holstein cows; 45,878 genotyped SNPs
- Population
- Contemporary US Holstein cattle with predicted transmitting abilities
- Outcome
- Additive SNP associations with production, health, and reproduction traits
Structured fields used in claim comparison tables when every cited study has a complete layer.
Key findings
Thousands of genome-wide significant additive effects; many top SNPs fall in genes; some SNPs are pleiotropic.
Methodology
Tested ~46k SNPs for additive effects on PTA traits and ranked top associations per trait.
Limitations
PTA-based phenotypes are processed breeding values, not raw farm records.
How this study connects
Role on claims
Each row is a claim on a concept or method page where this paper supports, challenges, or qualifies the statement. Roles are hand-checked — not a model guess.
Polygenic score accuracy can differ a lot among groups that share a broad ancestry label.
Polygenic score accuracy can differ substantially among groups that share a broad ancestry label; performance tracks ascertainment and SES-related structure, not ancestry labels alone.
Scope note — different species and trait system — dairy cattle GWAS, not human PGS accuracy
Limits the claim's scope: a different population, assay, or outcome.
Rare variants can create synthetic GWAS signals at common markers when clustered.
Rare variants can collectively create synthetic genome-wide association signals at common markers when they are not extremely numerous and evenly spread—so a GWAS peak is not automatically a single common causal allele.
Scope note — empirical cattle GWAS peaks — not a synthetic-signal simulation
Limits the claim's scope: a different population, assay, or outcome.
Large dairy GWAS recover many additive SNP effects, some in genes and some elsewhere.
Large GWAS of Holstein dairy traits recovered thousands of genome-wide significant additive effects, with many top SNPs in genes and some SNPs associated with multiple traits (pleiotropy).
Evidence for the claim as stated.
Human PGS accuracy, liver eQTLs, rare-variant synthetic-signal theory, livestock/plant GWAS, and microbiome–cancer MR all live under a GWAS umbrella, but they answer different estimands. Pooling them as one “GWAS finding” erases species, trait, and method limits.
Evidence for the claim as stated.
Crop and livestock GWAS in this set return many significant markers, LD that stretches for hundreds of kilobases, and networks rather than single genes. A soybean protein/oil scan used 31,954 QC SNPs covering about 86% of the genome, with euchromatic LD (r²) falling to 0.2 by about 360 kbp and protein ranging roughly 35–50% across accessions; a later 809-accession soybean scan tied GWAS loci into agronomic networks; a Holstein scan of ~46k SNPs across 31 PTA traits found thousands of genome-wide significant additive effects and pleiotropic SNPs.
Evidence for the claim as stated.
Phenotype quality differs. Holstein analyses use processed predicted transmitting abilities, not raw farm records; soybean protein/oil was measured in limited field environments; liver eQTLs are expression, not disease. Hits inherit those phenotype choices.
Evidence for the claim as stated.
Open questions
Tensions this paper is part of
From concept pages' “where studies disagree.” Disagreement means the same question; scope means different assays, populations, or outcomes.
Human PGS accuracy, liver eQTLs, rare-variant synthetic-signal theory, livestock/plant GWAS, and microbiome–cancer MR all live under a GWAS umbrella, but they answer different estimands. Pooling them as one “GWAS finding” erases species, trait, and method limits.
Phenotype quality differs. Holstein analyses use processed predicted transmitting abilities, not raw farm records; soybean protein/oil was measured in limited field environments; liver eQTLs are expression, not disease. Hits inherit those phenotype choices.
- Supports · Soybean GWAS for protein and oil
- Supports · Genetics of gene expression in human liver
History
When this study was placed
Dated entries from the concept change log — when this paper was added or removed as support, challenge, or qualifier on a claim.
Placed as a scope qualifier on GWAS
Polygenic score accuracy can differ substantially among groups that share a broad ancestry label; performance tracks ascertainment and SES-related structure, not ancestry labels alone.
Placed as a scope qualifier on GWAS
Rare variants can collectively create synthetic genome-wide association signals at common markers when they are not extremely numerous and evenly spread—so a GWAS peak is not automatically a single common causal allele.
Placed as supporting evidence on GWAS
Large GWAS of Holstein dairy traits recovered thousands of genome-wide significant additive effects, with many top SNPs in genes and some SNPs associated with multiple traits (pleiotropy).
Placed as supporting evidence on GWAS
Human PGS accuracy, liver eQTLs, rare-variant synthetic-signal theory, livestock/plant GWAS, and microbiome–cancer MR all live under a GWAS umbrella, but they answer different estimands. Pooling them as one “GWAS finding” erases species, trait, and method limits.
Related papers in this topic
Same topic cluster — not a recommendation engine.