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Tropical forage grasses, particularly those belonging to the Urochloa genus, play a crucial role in cattle production and serve as the main food source for animals in tropical and subtropical regions. The majority of these species are apomictic and tetraploid, highlighting the significance of U. ruziziensis, a sexual diploid species that can be tetraploidized for use in interspecific crosses with apomictic species. As a means to support breeding programs, our study investigates the feasibility of genome-wide family prediction in U. ruziziensis families to predict agronomic traits. Fifty half-sibling families were assessed for green matter yield, dry matter yield, regrowth capacity, leaf dry matter, and stem dry matter across different clippings established in contrasting seasons with varying available water capacity. Genotyping was performed using a genotyping-by-sequencing approach based on DNA samples from family pools. In addition to conventional genomic prediction methods, machine learning and feature selection algorithms were employed to reduce the necessary number of markers for prediction and enhance predictive accuracy across phenotypes. To explore the regulation of agronomic traits, our study evaluated the significance of selected markers for prediction using a tree-based approach, potentially linking these regions to quantitative trait loci (QTLs). In a multiomic approach, genes from the species transcriptome were mapped and correlated to those markers. A gene coexpression network was modeled with gene expression estimates from a diverse set of U. ruziziensis genotypes, enabling a comprehensive investigation of molecular mechanisms associated with these regions. The heritabilities of the evaluated traits ranged from 0.44 to 0.92. A total of 28,106 filtered SNPs were used to predict phenotypic measurements, achieving a mean predictive ability of 0.762. By employing feature selection techniques, we could reduce the dimensionality of SNP datasets, revealing potential genotype-phenotype associations. The functional annotation of genes near these markers revealed associations with auxin transport and biosynthesis of lignin, flavonol, and folic acid. Further exploration with the gene coexpression network uncovered associations with DNA metabolism, stress response, and circadian rhythm. These genes and regions represent important targets for expanding our understanding of the metabolic regulation of agronomic traits and offer valuable insights applicable to species breeding. Our work represents an innovative contribution to molecular breeding techniques for tropical forages, presenting a viable marker-assisted breeding approach and identifying target regions for future molecular studies on these agronomic traits.

The world population is expected to be larger and wealthier over the next few decades and will require more animal products, such as milk and beef. Tropical regions have great potential to meet this growing global demand, where pasturelands play a major role in supporting increased animal production. Better forage is required in consonance with improved sustainability as the planted area should not increase and larger areas cultivated with one or a few forage species should be avoided. Although, conventional tropical forage breeding has successfully released well-adapted and high-yielding cultivars over the last few decades, genetic gains from these programs have been low in view of the growing food demand worldwide. To guarantee their future impact on livestock production, breeding programs should leverage genotyping, phenotyping, and envirotyping strategies to increase genetic gains. Genomic selection (GS) and genome-wide association studies play a primary role in this process, with the advantage of increasing genetic gain due to greater selection accuracy, reduced cycle time, and increased number of individuals that can be evaluated. This strategy provides solutions to bottlenecks faced by conventional breeding methods, including long breeding cycles and difficulties to evaluate complex traits. Initial results from implementing GS in tropical forage grasses (TFGs) are promising with notable improvements over phenotypic selection alone. However, the practical impact of GS in TFG breeding programs remains unclear. The development of appropriately sized training populations is essential for the evaluation and validation of selection markers based on estimated breeding values. Large panels of single-nucleotide polymorphism markers in different tropical forage species are required for multiple application targets at a reduced cost. In this context, this review highlights the current challenges, achievements, availability, and development of genomic resources and statistical methods for the implementation of GS in TFGs. Additionally, the prediction accuracies from recent experiments and the potential to harness diversity from genebanks are discussed. Although, GS in TFGs is still incipient, the advances in genomic tools and statistical models will speed up its implementation in the foreseeable future. All TFG breeding programs should be prepared for these changes.

Abstract Background Forage species of Urochloa are planted in millions of hectares of tropical and subtropical pastures in South America. Most of the planted area is covered with four species (U. ruziziensis, U. brizantha, U. decumbens and U. humidicola). Breeding programs rely on interspecific hybridizations to increase genetic diversity and introgress traits of agronomic importance. Knowledge of phylogenetic relationships is important to optimize compatible hybridizations in Urochloa, where phylogeny has been subject of some controversy. We used next-generation sequencing to assemble the chloroplast genomes of four Urochloa species to investigate their phylogenetic relationships, compute their times of divergence and identify chloroplast DNA markers (microsatellites, SNPs and InDels). Results Whole plastid genome sizes were 138,765 bp in U. ruziziensis, 138,945 bp in U. decumbens, 138,946 bp in U. brizantha and 138,976 bp in U. humidicola. Each Urochloa chloroplast genome contained 130 predicted coding regions and structural features that are typical of Panicoid grasses. U. brizantha and U. decumbens chloroplast sequences are highly similar and show reduced SNP, InDel and SSR polymorphism as compared to U. ruziziensis and U. humidicola. Most of the structural and sequence polymorphisms were located in intergenic regions, and reflected phylogenetic distances between species. Divergence of U. humidicola from a common ancestor with the three other Urochloa species was estimated at 9.46 mya. U. ruziziensis, U. decumbens, and U. brizantha formed a clade where the U. ruziziensis lineage would have diverged by 5.67 mya, followed by a recent divergence event between U. decumbens and U. brizantha around 1.6 mya. Conclusion Low-coverage Illumina sequencing allowed the successful sequence analysis of plastid genomes in four species of Urochloa used as forages in the tropics. Pairwise sequence comparisons detected multiple microsatellite, SNP and InDel sites prone to be used as molecular markers in genetic analysis of Urochloa. Our results placed the origin of U. humidicola and U. ruziziensis divergence in the Miocene-Pliocene boundary, and the split between U. brizantha and U. decumbens in the Pleistocene.