ArticleBMC genomics2025
Mapping genes for resilient dairy cows by means of across-breed genome-wide association analysis.
Article in BMC genomics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundIndicator traits based on variance and autocorrelation of longitudinal data are increasingly used to measure resilience in animal breeding. While these traits show promising heritability and can be routinely collected, their genetic architecture remains poorly understood. We conducted GWAS for three resilience indicators across German Holstein (n = 2,300), Fleckvieh (n = 2,330), and Brown Swiss (n = 1,073) dairy cattle (Bos Taurus) populations. The indicators included variance ([Formula: see text]) and autocorrelation ([Formula: see text]) of deviations of observed from predicted daily milk yield and variance of relative daily milk yield ([Formula: see text]). Additionally, we analysed a selection index combining these traits. Prior to GWAS, we examined population structure through multi-dimensional scaling (MDS) and LD patterns, revealing distinct genetic clusters for each breed and similar LD decay patterns.
resultsThe GWAS results confirmed the polygenic nature of resilience, with multiple genomic regions showing significant associations. Notable signals were detected on BTA5 ([Formula: see text]), BTA14 ([Formula: see text]), BTA2 and BTA8 ([Formula: see text]) for single indicator traits. For selection index resilience, strong suggestive SNPs are located on BTA4, BTA16, BTA21, and BTA27. Detected regions overlapped with previously reported QTLs for performance, reproduction, longevity and health, providing new insights into the biological pathways underlying dairy cattle resilience.
conclusionsOur findings demonstrate that resilience indicators have a complex genetic architecture with both breed-specific and shared components, supporting their potential use in selective breeding programs while highlighting the importance of careful trait definition.
Indexed as
Identifiers
What Socratic 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 Socratic graph.