Accuracy of genomic selection for reducing susceptibility to pendulous crop in turkey (Meleagris gallopavo)
Bibliographic record
Abstract
Pendulous crop (PC) in the turkey occurs when the crop distends from its normal position, thereby preventing the movement of feed and water from the crop down into the digestive system. This condition negatively impacts the turkey industry at both production and welfare levels. In this study, we estimated the genetic parameters for PC incidence and its genetic correlation with 5 production traits. Additionally, we evaluated the prediction accuracy and bias of breeding values for the selection candidates using pedigree (BLUP) or pedigree-genomic (ssGBLUP) relationships among the animals. A total of 245,783 turkey records were made available by Hybrid Turkeys, Kitchener, Canada. Of these, 6,545 were affected with PC. In addition, the data included 9,634 records for breast meat yield (BMY); 5,592 records for feed conversion ratio (FCR) and residual feed intake (RFI) in males; 170,844 records for body weight (BW) and walking score (WS) between 18 and 20 wk of age for males (71,012) and females (99,832), respectively. Among this population, 36,830 were genotyped using a 65K SNP Illumina Inc. chip. While all animals passed the quality control criteria, only 53,455 SNP markers were retained for subsequent analysis. Heritability for PC was estimated at 0.16 ± 0.00 and 0.17 ± 0.00 using BLUP and ssGBLUP, respectively. The incidence of PC was not genetically correlated with WS or FCR. Low unfavourable genetic correlations with BW (0.12 and 0.14), BMY (0.24 and 0.24) and RFI (-0.33 and -0.28) were obtained using BLUP and ssGBLUP, respectively. Using ssGBLUP showed higher prediction accuracy (0.51) for the breeding values for the selection candidates than the pedigree-based model (0.35). Whereas the bias of the prediction was slightly reduced with ssGBLUP (0.33 ± 0.05) than BLUP (0.30 ± 0.08), both models showed a regression coefficient lower than one, indicating inflation in the predictions. The results of this study suggest that PC is a heritable trait and selection for lower PC incidence rates is feasible. Although further investigation is necessary, selection for BW, BMY, and RFI may increase PC incidence. Incorporating genomic information would lead to higher accuracy in predicting the genetic merit for selection candidates.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".