Genome-wide association study and in silico functional analysis of the number of embryos produced by Holstein donors
Bibliographic record
Abstract
Superovulation or ovum pick-up and in vitro fertilization are technologies used to produce an increased number of embryos from elite females. Embryo production traits have been shown to be heritable, but the genes that cause this variability have not yet been assessed. The main objectives of this study were to perform a genome-wide association study (GWAS) to find single nucleotide polymorphisms (SNP) associated with embryo production traits and to identify candidate genes affecting the number of embryos produced by Holstein donors in Canada that may provide insight into the regulation of embryo production. Breeding values were estimated and de-regressed for all donors and sires using a data set of 150,971 records of superovulation or ovum pick-up and in vitro fertilization. A total of 11,607 animals were genotyped, but of that number only 5,118 were genotyped with at least a 50K SNP panel and had a de-regressed estimated breeding value reliability of at least 10%. For the GWAS, 606,406 imputed SNP on 29 autosomal chromosomes were considered after applying quality control measures. A single-SNP univariate mixed linear animal model was used to perform the GWAS, and a 5% false discovery rate was applied to adjust for multiple testing. We found 36 and 14 significant SNP associated with the total number of embryos and the number of viable embryos, respectively, with most of them located on chromosome 11. Using these significant SNP, positional genes located within 10,000 bp upstream and downstream of the SNP were retrieved. Thirteen genes were harboring or near the significant SNP for the total number of embryos, 4 of them also being near the significant SNP for viable embryos. Some of these genes (CRB2, DENND1A, MAD1L1, NDUFA8, PTGS1) could be considered as potential positional candidate genes related to the number of embryos produced by a donor. This list will need to be validated in an independent population to confirm the role of the genes for embryo production.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".