An Overview of the Genetics and Genomics of the Urochloa Species Most Commonly Used in Pastures

Morpho-physiological and yield traits for selection of drought tolerant Urochloa grass ecotypes

Drought has become more recurrent and causes a substantial decline in forage yields leading to strain on feed resources for livestock production. This has intensified the search for drought-tolerant forages to promote sustainable livestock production. The objective of this study was to identify drought-tolerant Urochloa grasses and to discern their morpho-physiological and yield traits to water stress as well as the relationship between these traits and indices of drought resistance. The results showed that the ecotypes, water regimes and their interaction significantly influenced all the studied morpho-physiological and yield traits. There was a significant decrease in plant height, number of leaves and tillers, dry matter yield, relative water content, photosystem II and efficiency of photosystem II with an increase in non-photochemical quenching. The principal component analysis revealed that the performance of Urochloa grass ecotypes was different under water sufficient (WS) and water deficit conditions. Drought tolerance indicators (mean productivity, geometric mean productivity, tolerance index and stress tolerance index) were most effective in identifying Urochloa ecotypes with high biomass production under both water deficient and WS conditions. Ecotypes K17, K7, Kisii, Busia and Kakamega were the most drought tolerant, Basilisk, K6, K10, K19 and Toledo were moderately tolerant whereas, CIAT6385, CIAT16449, K13, K5 and K9 were drought sensitive. The five drought-tolerant Urochloa ecotypes should be tested for sustainable biomass production under field conditions and used in breeding programmes to develop high-yielding drought-tolerant varieties.

Phylogenomic analysis reveals five independently evolved African forage grass clades in the genus Urochloa

BACKGROUND AND AIMS

The grass genus Urochloa (Brachiaria) sensu lato includes forage crops that are important for beef and dairy industries in tropical and sub-tropical Africa, South America and Oceania/Australia. Economically important species include U. brizantha, U. decumbens, U. humidicola, U. mutica, U. arrecta, U. trichopus, U. mosambicensis and Megathyrsus maximus, all native to the African continent. Perennial growth habits, large, fast growing palatable leaves, intra- and interspecific morphological variability, apomictic reproductive systems and frequent polyploidy are widely shared within the genus. The combination of these traits probably favoured the selection for forage domestication and weediness, but trait emergence across Urochloa cannot be modelled, as a robust phylogenetic assessment of the genus has not been conducted. We aim to produce a phylogeny for Urochloa that includes all important forage species, and identify their closest wild relatives (crop wild relatives). Finally, we will use our phylogeny and available trait data to infer the ancestral states of important forage traits across Urochloa s.l. and model the evolution of forage syndromes across the genus.

METHODS

Using a target enrichment sequencing approach (Angiosperm 353), we inferred a species-level phylogeny for Urochloa s.l., encompassing 54 species (~40 % of the genus) and outgroups. Phylogenies were inferred using a multispecies coalescent model and maximum likelihood method. We determined the phylogenetic placement of agriculturally important species and identified their closest wild relatives, or crop wild relatives, based on well-supported monophyly. Further, we mapped key traits associated with Urochloa forage crops to the species tree and estimated ancestral states for forage traits along branch lengths for continuous traits and at ancestral nodes in discrete traits.

KEY RESULTS

Agricultural species belong to five independent clades, including U. brizantha and U. decumbens lying in a previously defined species complex. Crop wild relatives were identified for these clades supporting previous sub-generic groupings in Urochloa based on morphology. Using ancestral trait estimation models, we find that five morphological traits that correlate with forage potential (perennial growth habits, culm height, leaf size, a winged rachis and large seeds) independently evolved in forage clades.

CONCLUSIONS

Urochloa s.l. is a highly diverse genus that contains numerous species with agricultural potential, including crop wild relatives that are currently underexploited. All forage species and their crop wild relatives naturally occur on the African continent and their conservation across their native distributions is essential. Genomic and phenotypic diversity in forage clade species and their wild relatives need to be better assessed both to develop conservation strategies and to exploit the diversity in the genus for improved sustainability in Urochloa cultivar production.

Genome-wide family prediction unveils molecular mechanisms underlying the regulation of agronomic traits in Urochloa ruziziensis

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.

Advances in genomic characterization of Urochloa humidicola: exploring polyploid inheritance and apomixis

KEY MESSAGE

We present the highest-density genetic map for the hexaploid Urochloa humidicola. SNP markers expose genetic organization, reproduction, and species origin, aiding polyploid and tropical forage research. Tropical forage grasses are an important food source for animal feeding, with Urochloa humidicola, also known as Koronivia grass, being one of the main pasture grasses for poorly drained soils in the tropics. However, genetic and genomic resources for this species are lacking due to its genomic complexity, including high heterozygosity, evidence of segmental allopolyploidy, and reproduction by apomixis. These complexities hinder the application of marker-assisted selection (MAS) in breeding programs. Here, we developed the highest-density linkage map currently available for the hexaploid tropical forage grass U. humidicola. This map was constructed using a biparental F1 population generated from a cross between the female parent H031 (CIAT 26146), the only known sexual genotype for the species, and the apomictic male parent H016 (BRS cv. Tupi). The linkage analysis included 4873 single nucleotide polymorphism (SNP) markers with allele dosage information. It allowed mapping of the ASGR locus and apospory phenotype to linkage group 3, in a region syntenic with chromosome 3 of Urochloa ruziziensis and chromosome 1 of Setaria italica. We also identified hexaploid haplotypes for all individuals, assessed the meiotic configuration, and estimated the level of preferential pairing in parents during the meiotic process, which revealed the autopolyploid origin of sexual H031 in contrast to apomictic H016, which presented allopolyploid behavior in preferential pairing analysis. These results provide new information regarding the genetic organization, mode of reproduction, and allopolyploid origin of U. humidicola, potential SNPs markers associated with apomixis for MAS and resources for research on polyploids and tropical forage grasses.

Polyploid SNP Genotyping Using the MassARRAY System

Molecular marker discovery and genotyping are major challenges in polyploid breeding programs incorporating molecular biology tools. In this context, this work describes a method for single nucleotide polymorphism (SNP) genotyping in polyploid crops using matrix-assisted laser desorption ionization (MALDI) time-of-flight (TOF) mass spectrometry, the MassARRAY System.

Metabolic Engineering of Rice Cells with Vanillin Synthase Gene (VpVAN) to Produce Vanillin

Vanillin production by metabolic engineering of proprietary microbial strains has gained impetus due to increasing consumer demand for naturally derived products. Here, we demonstrate the use of rice cell cultures metabolically engineered with vanillin synthase gene (VpVAN) as a plant-based alternative to microbial vanillin production systems. VpVAN catalyzes the signature step to convert ferulic acid into vanillin in Vanilla planifolia. As ferulic acid is a phenylpropanoid pathway intermediate in plant cells, rice calli cells are ideal platform for in vivo vanillin synthesis due to the availability of its precursor. In this study, rice calli derived from embryonic rice cells were metabolically engineered with a codon-optimized VpVAN gene using Agrobacterium-mediated transformation. The putative transformants were selected based on their proliferation on herbicide-supplemented N6D medium. Expression of the transgenes were confirmed through a β-glucuronidase (GUS) reporter assay and polymerase chain reaction (PCR) analysis provided evidence of genetic transformation. The semiquantitative RT-PCR and real-time (RT)-qPCR revealed expression of VpVAN in six transgenic calli lines. High-performance liquid chromatography identified the biosynthesis of vanillin in transgenic calli lines, with the highest yielding line producing 544.72 (± 102.50) μg of vanillin^-g fresh calli. This work serves as a proof-of-concept to produce vanillin using metabolically engineered rice cell cultures.