ReviewBiology2026
Low-Coverage Whole-Genome Resequencing in Livestock and Poultry: Statistical Foundations, Applications and Future Directions.
Review in Biology, 2026. 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
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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.
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Authors and funding
8 authors.
Funding
Abstract
Low-coverage whole-genome resequencing (lcWGS) is emerging as a powerful population-scale genomic strategy for livestock and poultry research. By integrating sparse sequencing reads with genotype likelihoods, haplotype information and imputation models, lcWGS enables genome-wide variant discovery and genetic inference across large animal cohorts. This feature is particularly valuable for breeding populations, indigenous breeds and conservation resources, where broad sampling is essential for capturing population-specific variation and linking genomic diversity with economically and adaptively important traits. In this review, we synthesize the statistical foundations, analytical workflows and major applications of lcWGS in livestock and poultry genomics. We discuss how lcWGS supports genetic diversity assessment, population structure analysis, genome-wide association studies, genomic selection, selection-signature detection, environmental adaptation research and genetic resource conservation. We further highlight the importance of coordinated study design, including sequencing depth, sample size, reference-panel construction, imputation strategy, phenotype quality and downstream analytical models. Beyond its role as a cost-efficient genotyping approach, lcWGS provides a flexible framework for integrating population genomics with functional annotation, multi-omics resources, long-read assemblies, graph pan-genomes and interpretable prediction models. These developments are expanding the potential of lcWGS from variant discovery toward biological interpretation, precision breeding, climate-resilient animal production and the sustainable management of livestock and poultry genetic resources.
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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.