ReviewVeterinary medicine and science2026
Long Non-Coding RNAs: Key Regulators of Economic Traits in Livestock From Mechanisms to Breeding Applications.
Review in Veterinary medicine and science, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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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.
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Authors and funding
3 authors.
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Abstract
Long non-coding RNAs (lncRNAs) have emerged as critical regulators of economically important traits in livestock, including growth, reproduction, disease resistance and product quality. Unlike protein-coding genes, lncRNAs orchestrate gene expression at epigenetic, transcriptional and post-transcriptional levels, acting as molecular switches, scaffolds, decoys, and competing endogenous RNAs (ceRNAs). This review synthesises current knowledge on key lncRNA mechanisms such as ceRNA networks, liquid-liquid phase separation (LLPS) and RNA-targeting clustered regularly interspaced short palindromic repeats (CRISPR-Cas13) screening alongside trait-specific case studies in muscle hypertrophy (Callipyge locus), embryonic development (lnc_2217 in goats) and fecundity (ceRNA networks in sheep and chickens). We highlight the integration of lncRNAs with Genome Wide Association Studies (GWAS) data, where over 90% of trait-associated variants reside in non-coding regions, and propose a practical roadmap for functional validation and incorporation of lncRNAs into genomic selection and breeding programs. Harnessing lncRNA biology supported by recent functional annotation of animal genomes (FAANG) epigenomic maps and CRISPR-Cas13 applications in livestock, researchers will accelerate genetic gain in growth rate, marbling score, litter size and disease resilience, marking a paradigm shift toward precision livestock breeding.
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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.