47 Distortion of Mendelian segregation across Angus cattle genome reveal novel lethal haplotype affecting reproduction
Bibliographic record
Abstract
Abstract The rapid development of DNA technologies, together with the adoption and daily routine use of commercial SNP arrays in livestock industries, provided a valuable resource of large and powerful data that can be explored for innovative applications for animal breeding purposes. Thus, the current availability of trios (i.e., sire-dam-offspring) of genotyped families enables the implementation of the transmission ratio distortion (TRD) approach to discover lethal alleles. Lethal alleles, which are crucial genetic determinants for reproduction, do not follow Mendelian principles but deviate from inheritance expectations, displaying signals of TRD. In this research, TRD was characterized using allelic (specific- and unspecific-parent TRD) and genotypic parameterizations (additive- and dominance-TRD) using both SNP- and haplotype-based methods. The analyses were performed using 258,140 Angus animals with 92,942 autosomal SNP genotypes, including 7,486 sires, 72,688 dams and 205,966 offspring. Across the whole genome, 852 regions displaying TRD were identified with different statistical significance. Among these findings, 19 haplotypes with recessive patterns (potential lethality for homozygote individuals) and 52 genomic regions with allelic patterns exhibiting complete or quasi-complete absence for homozygous individuals in addition to under-representation (potentially reduced viability) of heterozygous offspring were found. The average number of under-represented offspring (i.e., expected but not observed) across 52 allelic TRD regions ranged from 5,000 to 41,008. In contrast, the number of non-observed homozygous offspring for the 19 regions with recessive pattern ranges from 10 to 564. In addition, 64 and 20 genomic regions with TRD showed significant effects on the trait heifer pregnancy P < 0.05 and P < 0.01, respectively, reducing the progeny rate up to 15%. These novel findings in Angus present new candidate genomic regions putatively carrying lethal and semi-lethal alleles providing opportunities to reduce the rates of embryonic losses or death of offspring which could improve fertility and fitness in beef cattle populations.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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".