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Record W4381715933 · doi:10.1111/jbg.12813

Genome‐wide association studies for epistatic genetic effects on fertility and reproduction traits in Holstein cattle

2023· article· en· W4381715933 on OpenAlexafffund
Kristen Alves, Luiz F. Brito, Mehdi Sargolzaei, Flávio S. Schenkel

Bibliographic record

VenueJournal of Animal Breeding and Genetics · 2023
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetic and phenotypic traits in livestock
Canadian institutionsUniversity of GuelphBayer (Canada)
FundersAgriculture and Agri-Food CanadaDairy Farmers of Canada
KeywordsBiologyEpistasisSingle-nucleotide polymorphismGeneticsGenome-wide association studyGenetic architectureQuantitative trait locusSNPPopulationGenotypeGene

Abstract

fetched live from OpenAlex

Abstract Non‐additive genetic effects are well known to play an important role in the phenotypic expression of complex traits, such as fertility and reproduction. In this study, a genome scan was performed using 41,640 single nucleotide polymorphism (SNP) markers to identify genomic regions associated with epistatic (additive‐by‐additive) effects in fertility and reproduction traits in Holstein cattle. Nine fertility and reproduction traits were analysed on 5825 and 6090 Holstein heifers and cows with phenotypes and genotypes, respectively. The Marginal Epistasis Test (MAPIT) was used to identify SNPs with significant marginal epistatic effects at a chromosome‐wise 5% and 10% false discovery rate (FDR) level. The −log 10 ( p ) values were adjusted by the genomic inflation factor (λ) to correct for the potential bias on the p ‐values and minimize the possible effects of population stratification. After adjustments, MAPIT enabled the identification of genomic regions with significant marginal epistatic effects for heifers on BTA5 for age at first insemination, BTA3 and BTA24 for non‐return rate (NRR); BTA16 and BTA28 for gestation length (GL); BTA1, BTA4 and BTA17 for stillbirth (SB). For the cow traits, MAPIT enabled the identification of regions on BTA11 for GL, BTA11 and BTA16 for SB and BTA19 for calf size (CZ). An additional approach for mapping epistasis in a genome‐wide association study was also proposed, in which the genome scan was performed using estimates of epistatic values as the input pseudo‐phenotypes, computed using single‐trait animal models. Significant SNPs were identified at the chromosome‐wise 5% and 10% FDR levels for all traits. For the heifer traits, significant regions were found on BTA7 for AFS; BTA12 for NRR; BTA14 and BTA19 for GL; BTA19 for calving ease (CE); BTA5, BTA24, BTA25 and in the X chromosome for SB; BTA23 and in the X chromosome for CZ and in the X chromosome for the number of services (NS). For the cow traits, significant regions were found on BTA29 and in the X chromosome for NRR, BTA11, BTA16 and in the X chromosome for SB, BTA2 for GL, BTA28 for CZ, BTA19 for calving to first insemination, and in the X chromosome for NS and first insemination to conception. The results suggest that the epistatic genetic effects are likely due to many loci with a small effect rather than few loci with a large effect and/or a single SNP marker alone do not capture the epistatic effects well. The genomic architecture of fertility and reproduction traits is complex, and these results should be validated in independent dairy cattle populations and using alternative statistical models.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.771
Threshold uncertainty score0.465

Codex and Gemma teacher scores by category

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

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 head0.027
GPT teacher head0.287
Teacher spread0.260 · 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 teacher head, 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

Citations9
Published2023
Admission routes2
Has abstractyes

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