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.

Post-operative Rehabilitation in Klatskin Tumor: A Rare Case Report.

Cholangiocarcinoma (CCA), commonly referred to as Klatskin tumor (KT), is a rare cancer that develops from the epithelium of the intra- or extrahepatic bile duct. This case outlines the impact of physiotherapy rehabilitation in a post-operative case of a KT in a 58-year-old male who presented with complaints of abdominal pain, nausea, constipation, and difficulty in urinating and reportedly exhibited generalized weakness, weight loss, and dyspnea. Following investigations such as computed tomography (CT) scan, the patient was diagnosed with a KT for which he underwent hepaticojejunostomy and was kept under observation, following which supervised physiotherapy intervention (PI) commenced from post-operative day (POD) 3. The outcome measure was peak expiratory flow rate (PEFR), whereas the intervention involved diaphragmatic breathing exercises (DBEs), thoracic expansion exercises (TEEs), incentive spirometry (IS), range of motion (ROM) exercises, active cycle of breathing technique (ACBT), and ambulation. After two weeks of treatment, there were an improvement in cough frequency and an appreciable change in vital capacity (VC), and a significant increase in PEFR values was observed.

Introduction of gloved hand to cage induces 22-kHz ultrasonic vocalizations in male albino rats.

Rodents emit ultrasonic vocalizations (USVs) above the human hearing threshold of ~ 20 kHz to communicate emotional states and to coordinate their social interactive behavior. Twenty-two kHz USVs emitted by adult rats have been reported in a variety of aversive social and behavioral situations. They occur not only under painful or restraining conditions but can also be evoked by gentle cutaneous touch or airflow. This study aimed to test if placement of a human hand in a cage can evoke 22-kHz USVs. It was found that 36% of the adult male Sprague-Dawley and 13% of the adult male Wistar Han rats emitted 22-kHz USVs when a gloved hand was introduced into the cages. Average vocalization onset latencies were 5.0 ± 4.4 s (Sprague-Dawley) and 7.4 ± 4.0 s (Wistar Han) and the USVs had a stable frequency (22 kHz) across the calls, ranging from 0.1 to 2.3 seconds in duration. Surprisingly, no 22-kHz USVs were found in any female Wistar Han rats tested. To further explore the mechanisms underlying this observation, we compared retinal function, basal serum corticosterone, and testosterone levels between the 22-kHz USV responders and non-responders. None of these parameters or endpoints showed any significant differences between the two cohorts. The results suggest that the introduction of a gloved-hand inside the cage can trigger adult male albino rats to emit 22-kHz ultrasonic vocalizations. This response should be considered in USV studies and animal welfare.

A joint learning approach for genomic prediction in polyploid grasses.

Poaceae, among the most abundant plant families, includes many economically important polyploid species, such as forage grasses and sugarcane (Saccharum spp.). These species have elevated genomic complexities and limited genetic resources, hindering the application of marker-assisted selection strategies. Currently, the most promising approach for increasing genetic gains in plant breeding is genomic selection. However, due to the polyploidy nature of these polyploid species, more accurate models for incorporating genomic selection into breeding schemes are needed. This study aims to develop a machine learning method by using a joint learning approach to predict complex traits from genotypic data. Biparental populations of sugarcane and two species of forage grasses (Urochloa decumbens, Megathyrsus maximus) were genotyped, and several quantitative traits were measured. High-quality markers were used to predict several traits in different cross-validation scenarios. By combining classification and regression strategies, we developed a predictive system with promising results. Compared with traditional genomic prediction methods, the proposed strategy achieved accuracy improvements exceeding 50%. Our results suggest that the developed methodology could be implemented in breeding programs, helping reduce breeding cycles and increase genetic gains.

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

Pastures based on perennial monocotyledonous plants are the principal source of nutrition for ruminant livestock in tropical and subtropical areas across the globe. The Urochloa genus comprises important species used in pastures, and these mainly include Urochloa brizantha, Urochloa decumbens, Urochloa humidicola, and Urochloa ruziziensis. Despite their economic relevance, there is an absence of genomic-level information for these species, and this lack is mainly due to genomic complexity, including polyploidy, high heterozygosity, and genomes with a high repeat content, which hinders advances in molecular approaches to genetic improvement. Next-generation sequencing techniques have enabled the recent release of reference genomes, genetic linkage maps, and transcriptome sequences, and this information helps improve our understanding of the genetic architecture and molecular mechanisms involved in relevant traits, such as the apomictic reproductive mode. However, more concerted research efforts are still needed to characterize germplasm resources and identify molecular markers and genes associated with target traits. In addition, the implementation of genomic selection and gene editing is needed to reduce the breeding time and expenditure. In this review, we highlight the importance and characteristics of the four main species of Urochloa used in pastures and discuss the current findings from genetic and genomic studies and research gaps that should be addressed in future research.

A Semi-Automated SNP-Based Approach for Contaminant Identification in Biparental Polyploid Populations of Tropical Forage Grasses.

Artificial hybridization plays a fundamental role in plant breeding programs since it generates new genotypic combinations that can result in desirable phenotypes. Depending on the species and mode of reproduction, controlled crosses may be challenging, and contaminating individuals can be introduced accidentally. In this context, the identification of such contaminants is important to avoid compromising further selection cycles, as well as genetic and genomic studies. The main objective of this work was to propose an automated multivariate methodology for the detection and classification of putative contaminants, including apomictic clones (ACs), self-fertilized individuals, half-siblings (HSs), and full contaminants (FCs), in biparental polyploid progenies of tropical forage grasses. We established a pipeline to identify contaminants in genotyping-by-sequencing (GBS) data encoded as allele dosages of single nucleotide polymorphism (SNP) markers by integrating principal component analysis (PCA), genotypic analysis (GA) measures based on Mendelian segregation, and clustering analysis (CA). The combination of these methods allowed for the correct identification of all contaminants in all simulated progenies and the detection of putative contaminants in three real progenies of tropical forage grasses, providing an easy and promising methodology for the identification of contaminants in biparental progenies of tetraploid and hexaploid species. The proposed pipeline was made available through the polyCID Shiny app and can be easily coupled with traditional genetic approaches, such as linkage map construction, thereby increasing the efficiency of breeding programs.

High-Resolution Linkage Map With Allele Dosage Allows the Identification of Regions Governing Complex Traits and Apospory in Guinea Grass (Megathyrsus maximus).

Forage grasses are mainly used in animal feed to fatten cattle and dairy herds, and guinea grass (Megathyrsus maximus) is considered one of the most productive of the tropical forage crops that reproduce by seeds. Due to the recent process of domestication, this species has several genomic complexities, such as autotetraploidy and aposporous apomixis. Consequently, approaches that relate phenotypic and genotypic data are incipient. In this context, we built a linkage map with allele dosage and generated novel information of the genetic architecture of traits that are important for the breeding of M. maximus. From a full-sib progeny, a linkage map containing 858 single nucleotide polymorphism (SNP) markers with allele dosage information expected for an autotetraploid was obtained. The high genetic variability of the progeny allowed us to map 10 quantitative trait loci (QTLs) related to agronomic traits, such as regrowth capacity and total dry matter, and 36 QTLs related to nutritional quality, which were distributed among all homology groups (HGs). Various overlapping regions associated with the quantitative traits suggested QTL hotspots. In addition, we were able to map one locus that controls apospory (apo-locus) in HG II. A total of 55 different gene families involved in cellular metabolism and plant growth were identified from markers adjacent to the QTLs and APOSPORY locus using the Panicum virgatum genome as a reference in comparisons with the genomes of Arabidopsis thaliana and Oryza sativa. Our results provide a better understanding of the genetic basis of reproduction by apomixis and traits important for breeding programs that considerably influence animal productivity as well as the quality of meat and milk.

Corrigendum: Genetic Mapping With Allele Dosage Information in Tetraploid Urochloa decumbens (Stapf) R. D. Webster Reveals Insights Into Spittlebug (Notozulia entreriana Berg) Resistance.

[This corrects the article DOI: 10.3389/fpls.2019.00092.].

Genetic Mapping With Allele Dosage Information in Tetraploid Urochloa decumbens (Stapf) R. D. Webster Reveals Insights Into Spittlebug (Notozulia entreriana Berg) Resistance.

Urochloa decumbens (Stapf) R. D. Webster is one of the most important African forage grasses in Brazilian beef production. Currently available genetic-genomic resources for this species are restricted mainly due to polyploidy and apomixis. Therefore, crucial genomic-molecular studies such as the construction of genetic maps and the mapping of quantitative trait loci (QTLs) are very challenging and consequently affect the advancement of molecular breeding. The objectives of this work were to (i) construct an integrated U. decumbens genetic map for a full-sibling progeny using GBS-based markers with allele dosage information, (ii) detect QTLs for spittlebug (Notozulia entreriana) resistance, and (iii) seek putative candidate genes involved in defense against biotic stresses. We used the Setaria viridis genome a reference to align GBS reads and selected 4,240 high-quality SNP markers with allele dosage information. Of these markers, 1,000 were distributed throughout nine homologous groups with a cumulative map length of 1,335.09 cM and an average marker density of 1.33 cM. We detected QTLs for resistance to spittlebug, an important pasture insect pest, that explained between 4.66 and 6.24% of the phenotypic variation. These QTLs are in regions containing putative candidate genes related to defense against biotic stresses. Because this is the first genetic map with SNP autotetraploid dosage data and QTL detection in U. decumbens, it will be useful for future evolutionary studies, genome assembly, and other QTL analyses in Urochloa spp. Moreover, the results might facilitate the isolation of spittlebug-related candidate genes and help clarify the mechanism of spittlebug resistance. These approaches will improve selection efficiency and accuracy in U. decumbens molecular breeding and shorten the breeding cycle.

Population Structure and Genetic Diversity of Sweet Cassava Accessions from the Midwestern, Southeastern and Southern Regions of Brazil

Abstract The objective of this work was to screen sweet cassava accessions collected in smallholding areas in the Midwestern, Southeastern and Southern regions of Brazil, using 15 SSR molecular markers, to determine population structure and genetic diversity. Polymorphism was detected in every loci analyzed, with mean of 6.33 alleles per locus, and mean polymorphism information content (PIC) of 0.6057, pointing out that the primers were highly informative. The observed heterozygosity ranged from 0.0709 (SSRY 101) to 0.9398 (GA 12), with a mean of 0.6511, and mean genetic diversity of 0.6578, ranging from 0.3592 (GA 136) to 0.8116 (SSRY 21). The most dissimilar combinations observed were BGM526PR-BGM596MS, BGM526PR-BGM622MS and BGM526PR-BGM629MS. The traditional cassava cultivars assessed were divided into four distinct groups: two with cultivars from the South, one from the Southeast and one from the Midwestern region of Brazil. The variances among and within groups determined by the analysis of molecular variance were 44 and 56%, respectively. The PhiPT parameter (analogue to Fst) of 0.44 indicates high differentiation among groups. Broad genetic diversity was found among the traditional sweet cassava cultivars assessed, and the most divergent groups were formed by cultivars from the South and the Midwestern regions of Brazil.

Microsatellite loci for Urochloa decumbens (Stapf) R.D. Webster and cross-amplification in other Urochloa species.

BACKGROUND: Forage grasses of the African genus Urochloa (syn. Brachiaria) are the basis of Brazilian beef production, and there is a strong demand for high quality, productive and adapted forage plants. Among the approximately 100 species of the genus Urochloa, Urochloa decumbens is one of the most important tropical forage grasses used for pastures due to several of its agronomic attributes. However, the level of understanding of these attributes and the tools with which to control them at the genetic level are limited, mainly due to the apomixis and ploidy level of this species. In this context, the present study aimed to identify and characterize molecular microsatellite markers of U. decumbens and to evaluate their cross-amplification in other Urochloa species. FINDINGS: Microsatellite loci were isolated from a previously constructed enriched library from one U. decumbens genotype. Specific primers were designed for one hundred thirteen loci, and ninety-three primer pairs successfully amplified microsatellite regions, yielding an average of 4.93 alleles per locus. The polymorphism information content (PIC) values of these loci ranged from 0.26 to 0.85 (average 0.68), and the associated discriminating power (DP) values ranged from 0.22 to 0.97 (average 0.77). Cross-amplification studies demonstrated the potential transferability of these microsatellites to four other Urochloa species. Structure analysis revealed the existence of three distinct groups, providing evidence in the allelic pool that U. decumbens is closely related to Urochloa ruziziensis and Urochloa brizantha. The genetic distance values determined using Jaccard's coefficient ranged from 0.06 to 0.76. CONCLUSIONS: The microsatellite markers identified in this study are the first set of molecular markers for U. decumbens species. Their availability will facilitate understanding the genetics of this and other Urochloa species and breeding them, and will be useful for germplasm characterization, linkage mapping and marker-assisted selection.