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Linkage disequilibrium and signatures of selection on chromosomes 19 and 29 in beef and dairy cattle

2008· article· en· W2111932499 on OpenAlexaff
Aparna Prasad, Robert D. Schnabel, Stephanie McKay, Brenda M. Murdoch, Paul Stothard, D. Kolbehdari, Z. Wang, John F. Taylor, S. S. Moore

Bibliographic record

VenueAnimal Genetics · 2008
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetic and phenotypic traits in livestock
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsBiologyLinkage disequilibriumGeneticsBovine genomeBeef cattleSingle-nucleotide polymorphismLocus (genetics)Dairy cattleGenetic associationDisequilibriumSelection (genetic algorithm)GenomeGenotypeGene

Abstract

fetched live from OpenAlex

The objective of this study was to quantify the extent of linkage disequilibrium (LD) on bovine chromosomes 19 and 29 and to study the pattern of selection signatures in beef and dairy breeds (Angus and Holstein) of Bos taurus. The extent of LD was estimated for 370 and 186 single nucleotide polymorphism markers on BTA19 and 29 respectively using the square of the correlation coefficient (r(2)) among alleles at pairs of loci. A comparison of the extent of LD found that the decline of LD followed a similar pattern in both breeds. We observed long-range LD and found that LD dissipates to background levels at a locus separation of about 20 Mb on both chromosomes. Along each chromosome, patterns of LD were variable in both breeds. We find that a minimum of 30 000 informative and evenly spaced markers would be required for whole-genome association studies in cattle. In addition, we have identified chromosomal regions that show some evidence of selection for economically important traits in Angus and Holstein cattle. The results of this study are of importance for the design and application of association studies.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.012
GPT teacher head0.235
Teacher spread0.224 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations41
Published2008
Admission routes1
Has abstractyes

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