ArticleGenes2025
Accuracy of Genomic Predictions for Resistance to Gastrointestinal Parasites in Australian Merino Sheep.
Article in Genes, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
2 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Pooled it
- Epidemiological landscape and genetic prospects for marker-assisted selection in Kazakh sheep.Frontiers in veterinary science · 2025Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
Abstract
Infection by gastrointestinal nematodes (GINs) in sheep is a significant health issue that affects animal welfare and leads to economic losses in the production sector. Genetic selection for parasite resistance has shown promise in improving animal health and productivity. This study aimed to determine if incorporating genomic data into genetic prediction models currently used in Uruguay could improve the accuracy of breeding value estimations for GIN resistance in the Australian Merino breed. This study compared the accuracy of breeding value predictions using the BLUP (Best Linear Unbiased Prediction) and ssGBLUP (single-step genomic BLUP) models on partial and complete data sets, including 32,713 phenotyped and 3238 genotyped animals. The quality of predictions was evaluated using a linear regression method, focusing on 145 rams. The inclusion of genomic data increased the average individual accuracies by 4% for genotyped and phenotyped animals. For animals with genomic and non-phenotyped data, the accuracy improvement reached 8%. Of these, one group of animals that benefited from an ssGBLUP evaluation came from a facility with a strong connection to the informative nucleus and showed an average increase of 20% in their individual accuracy. Additionally, ssGBLUP slightly outperformed BLUP in terms of prediction quality. These findings demonstrate the potential of genomic information to improve the accuracy of breeding value predictions for parasite resistance in sheep. The integration of genomic data, particularly in non-phenotyped animals, offers a promising tool for enhancing genetic selection in Australian Merino sheep to improve resistance to gastrointestinal parasites.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.