Comparative genomics and reproductive mechanisms of fertility in cattle and camels: Implications for assisted reproduction and precision breeding.

Fertility limits productivity in cattle and camels. Bovine fertility genomics is advanced, but determinants of fertility in camels remain poorly defined. Advances in long-read assemblies, transcriptomics, multi-omics, and biotechnology provide opportunities to resolve species-specific mechanisms and improve assisted reproductive technologies (ART). This review synthesizes genomic, molecular, endocrine, and biotechnological evidence to evaluate ART and precision breeding strategies. A structured search (2010-2025) across databases retrieved studies reporting molecular, genetic, physiological, or ART evidence related to fertility, enabling cross-species comparisons. Study quality and relevance were appraised, and findings were synthesized narratively with emphasis on translational relevance for breeding and herd management. In cattle, FSHR, LHCGR, IGF1, LEP/LEPR, BMP15, and GDF9 show consistent support from genome-wide association studies (GWAS), transcriptomics, and functional assays. In camels, preliminary evidence implicates FSHR, LHCGR, STAR, CYP19A1, BMP15, GDF9, and ESR1. The hypothalamic-pituitary-gonadal axis, gonadotropin signaling, PI3K-AKT and TGF-β cascades, steroidogenesis, epigenetic regulation, and oocyte-derived factors. Comparative analysis indicates conserved genes but distinct features of induced ovulation, seasonality, and endocrine control in camels. Emerging tools-long-read assemblies, RNA-seq, single-cell omics, CRISPR, and AI-based prediction-are promising. Assisted Reproductive Technologies (IVF/ICSI, OPU-IVEP, embryo grading, hormonal synchronization) is well established in cattle but still developing in camels. We conclude that cattle fertility genomics is robust, whereas camel genomics remain fragmented. Integrating genomic data, reproductive physiology, and ART can accelerate genetic gain. Priorities include camel SNP arrays (genome-wide SNP genotyping platforms), multi-omics datasets, improved ART outcomes, Artificial Intelligence/Machine Learning phenotyping and prediction, supported by coordinated regional and international collaborations to enhance reproductive management in arid systems.