A Semi-Automated SNP-Based Approach for Contaminant Identification in Biparental Polyploid Populations of Tropical Forage Grasses
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ABSTRACT:
SUBMITTER: Martins F
PROVIDER: S-EPMC8569613 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Periods of soil water stress have been recurrent in the Cerrado region and have become a growing concern for Brazilian tropical pasture areas. Thus, the search for forage grasses more tolerant to water stress has intensified recently in order to promote more sustainable livestock. In a greenhouse experiment, the degree of water stress tolerance of nine tropical forage grass cultivars was studied under different soil water regimes. The investigation followed a 9 × 3 factorial design in four randomized blocks. Nine cultivars from five species of perennial forage grasses were tested: Urochloa brizantha ('BRS Piatã', 'Marandu', and 'Xaraés'), Panicum maximum ('Aruana', 'Mombaça', and 'Tanzânia'), Pennisetum glaucum ('ADR 300'), Urochloa ruziziensis ('Comum'), and Paspalum atratum ('Pojuca'). These cultivars were grown in pots under three soil water regimes (high soil water regime-HSW (non-stressful condition), middle soil water regime-MSW (moderate water stress), and low soil water regime-LSW (severe water stress)). Plants were exposed to soil water stress for 25 days during the tillering and stalk elongation phases. Twelve tolerance indices, including tolerance index (TOL), mean production (MP), yield stability index (YSI), drought resistance index (DI), stress tolerance index (STI), geometric mean production (GMP), yield index (YI), modified stress tolerance (k1STI and k2STI), stress susceptibility percentage index (SSPI), abiotic tolerance index (ATI), and harmonic mean (HM), were calculated based on shoot biomass production under non-stressful (YP) and stressful (YS) conditions. Soil water stress decreased leaf area, plant height, tillering capacity, root volume, and shoot and root dry matter production in most cultivars, with varying degrees of reduction among tropical forage grasses. Based on shoot biomass production under controlled greenhouse conditions, the most water-stress-tolerant cultivars were P. maximum cv. Mombaça and cv. Tanzânia under the MSW regime and P. maximum cv. Aruana and cv. Mombaça under the LSW regime. P. maximum cv. Mombaça has greater adaptability and stability of shoot biomass production when grown under greenhouse conditions and subjected to soil water stress. Therefore, this forage grass should be tested under field conditions to confirm its forage production potential for cultivation in tropical regions with the occurrence of water stress. The MP, DI, STI, GMP, YI, k2STI, and HM tolerance indices were the most suitable for identifying forage grass cultivars with greater water stress tolerance and a high potential for shoot biomass production under LSW regime.
| S-EPMC9504478 | biostudies-literature
Project description:Drought severely limits forage productivity of C4 grasses across the tropics. The avoidance of water deficit by increasing the capacity for water uptake or by controlling water loss are common responses in forage C4 grasses. Napier grass (Pennisetum purpureum) and Brachiaria hybrid cv. Mulato II are tropical C4 grasses used for livestock production due to their reputed resistance to drought conditions. However, there is scant information on the mechanisms used by these grasses to overcome water-limited conditions. Therefore, assessments of cumulative transpired water, shoot growth, leaf rolling, leaf gas exchange, dry mass production and a number of morpho-physiological traits were recorded over a period of 21 days under well-watered or drought conditions. Drought reduced shoot dry mass of both grasses by 35 %, yet each grass exhibited contrasting strategies to cope with water shortage. Napier grass transpired most available water by the end of the drought treatment, whereas a significant amount of water was still available for Mulato II. Napier grass maintained carbon assimilation until the soil was fairly dry, whereas Mulato II restricted water loss by early stomatal closure at relatively wet soil conditions. Our results suggest that Napier grass exhibits a 'water-spending' behaviour that might be targeted to areas with intermittent drought stress, whereas Mulato II displays a 'water-saving' nature that could be directed to areas with longer dry periods.
| S-EPMC4595746 | biostudies-literature
Project description:Grasslands represent a critical ecosystem important for global food production, soil carbon storage, and water regulation. Current intensification and expansion practices add to the degradation of grasslands and dramatically increase greenhouse gas emissions and pollution. Thus, new ways to sustain and improve their productivity are needed. Research efforts focus on the plant-leaf microbiome, or phyllosphere, because its microbial members impact ecosystem function by influencing pathogen resistance, plant hormone production, and nutrient availability through processes including nitrogen fixation. However, little is known about grassland phyllospheres and their response to environmental stress. In this study, globally dominant temperate and tropical forage grass species were grown in a greenhouse under current climate conditions and drought conditions that mimic future climate predictions to understand if (i) plant host taxa influence microbial community assembly, (ii) microbial communities respond to drought stress, and (iii) phyllosphere community changes correlate to changes in plant host traits and stress-response strategies. Community analysis using high-resolution sequencing revealed Gammaproteobacteria as the dominant bacterial class, which increased under severe drought stress on both temperate and tropical grasses while overall bacterial community diversity declined. Bacterial community diversity, structure, and response to drought were significantly different between grass species. This community dependence on plant host species correlated with differences in grass species traits, which became more defined under drought stress conditions, suggesting symbiotic evolutionary relationships between plant hosts and their associated microbial community. Further understanding these strategies and the functions microbes provide to plants will help us utilize microbes to promote agricultural and ecosystem productivity in the future. IMPORTANCE Globally important grassland ecosystems are at risk of degradation due to poor management practices compounded by predicted increases in severity and duration of drought over the next century. Finding new ways to support grassland productivity is critical to maintaining their ecological and agricultural benefits. Discerning how grassland microbial communities change in response to climate stress will help us understand how plant-microbe relationships may be useful to sustainably support grasslands in the future. In this study, phyllosphere community diversity and composition were significantly altered under drought conditions. The significance of our research is demonstrating how severe climate stress reduces bacterial community diversity, which previously was directly associated with decreased plant productivity. These findings guide future questions about functional plant-microbe interactions under stress conditions, greatly enhancing our understanding of how bacteria can increase food security by promoting grassland growth and resilience.
| S-EPMC8357280 | biostudies-literature
Project description:Background and aimsThe C4Urochloa species (syn. Brachiaria) and Megathyrsus maximus (syn. Panicum maximum) are used as pasture for cattle across vast areas in tropical agriculture systems in Africa and South America. A key target for variety improvement is forage quality: enhanced digestibility could decrease the amount of land required per unit production, and enhanced lipid content could decrease methane emissions from cattle. For these traits, loss-of-function (LOF) alleles in known gene targets are predicted to improve them, making a reverse genetics approach of allele mining feasible. We therefore set out to look for such alleles in diverse accessions of Urochloa species and Megathyrsus maximus from the genebank collection held at the CIAT.MethodsWe studied allelic diversity of 20 target genes (11 for digestibility, nine for lipid content) in 104 accessions selected to represent genetic diversity and ploidy levels of U. brizantha, U. decumbens, U. humidicola, U. ruziziensis and M. maximum. We used RNA sequencing and then bait capture DNA sequencing to improve gene models in a U. ruziziensis reference genome to assign polymorphisms with high confidence.Key resultsWe found 953 non-synonymous polymorphisms across all genes and accessions; within these, we identified seven putative LOF alleles with high confidence, including those in the non-redundant SDP1 and BAHD01 genes present in diploid and tetraploid accessions. These LOF alleles could respectively confer increased lipid content and digestibility if incorporated into a breeding programme.ConclusionsWe demonstrated a novel, effective approach to allele discovery in diverse accessions using a draft reference genome from a single species. We used this to find gene variants in a collection of tropical grasses that could help reduce the environmental impact of cattle production.
| S-EPMC8422886 | biostudies-literature
Project description:BackgroundOur group studies the interactions between cells of the brain and the neurotropic parasite Toxoplasma gondii. Using an in vivo system that allows us to permanently mark and identify brain cells injected with Toxoplasma protein, we have identified that Toxoplasma-injected neurons (TINs) are heterogeneously distributed throughout the brain. Unfortunately, standard methods to quantify and map heterogeneous cell populations onto a reference brain atlas are time consuming and prone to user bias.New methodWe developed a novel MATLAB-based semi-automated quantification and mapping program to allow the rapid and consistent mapping of heterogeneously distributed cells on to the Allen Institute Mouse Brain Atlas. The system uses two-threshold background subtraction to identify and quantify cells of interest.ResultsWe demonstrate that we reliably quantify and neuroanatomically localize TINs with low intra- or inter-observer variability. In a follow up experiment, we show that specific regions of the mouse brain are enriched with TINs.Comparison with existing methodsThe procedure we use takes advantage of simple immunohistochemistry labeling techniques, use of a standard microscope with a motorized stage, and low cost computing that can be readily obtained at a research institute. To our knowledge there is no other program that uses such readily available techniques and equipment for mapping heterogeneous populations of cells across the whole mouse brain.ConclusionThe quantification method described here allows reliable visualization, quantification, and mapping of heterogeneous cell populations in immunolabeled sections across whole mouse brains.
| S-EPMC6357967 | biostudies-literature
Project description:This study evaluates the impact of N fertilizer on the soil microbiome with grasses
| PRJEB41425 | ENA
Project description: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.
| S-EPMC9304331 | biostudies-literature
Project description:Background and aimsDiploid and polyploid Urochloa (including Brachiaria, Panicum and Megathyrsus species) C4 tropical forage grasses originating from Africa are important for food security and the environment, often being planted in marginal lands worldwide. We aimed to characterize the nature of their genomes, the repetitive DNA and the genome composition of polyploids, leading to a model of the evolutionary pathways within the group including many apomictic species.MethodsSome 362 forage grass accessions from international germplasm collections were studied, and ploidy was determined using an optimized flow cytometry method. Whole-genome survey sequencing and molecular cytogenetic analysis were used to identify chromosomes and genomes in Urochloa accessions belonging to the 'brizantha' and 'humidicola' agamic complexes and U. maxima.Key resultsGenome structures are complex and variable, with multiple ploidies and genome compositions within the species, and no clear geographical patterns. Sequence analysis of nine diploid and polyploid accessions enabled identification of abundant genome-specific repetitive DNA motifs. In situ hybridization with a combination of repetitive DNA and genomic DNA probes identified evolutionary divergence and allowed us to discriminate the different genomes present in polyploids.ConclusionsWe suggest a new coherent nomenclature for the genomes present. We develop a model of evolution at the whole-genome level in diploid and polyploid accessions showing processes of grass evolution. We support the retention of narrow species concepts for Urochloa brizantha, U. decumbens and U. ruziziensis, and do not consider diploids and polyploids of single species as cytotypes. The results and model will be valuable in making rational choices of parents for new hybrids, assist in use of the germplasm for breeding and selection of Urochloa with improved sustainability and agronomic potential, and assist in measuring and conserving biodiversity in grasslands.
| S-EPMC9904353 | biostudies-literature
Project description:Intense structuring of plant breeding populations challenges the design of the training set (TS) in genomic selection (GS). An important open question is how the TS should be constructed from multiple related or unrelated small biparental families to predict progeny from individual crosses. Here, we used a set of five interconnected maize (Zea mays L.) populations of doubled-haploid (DH) lines derived from four parents to systematically investigate how the composition of the TS affects the prediction accuracy for lines from individual crosses. A total of 635 DH lines genotyped with 16,741 polymorphic SNPs were evaluated for five traits including Gibberella ear rot severity and three kernel yield component traits. The populations showed a genomic similarity pattern, which reflects the crossing scheme with a clear separation of full sibs, half sibs, and unrelated groups. Prediction accuracies within full-sib families of DH lines followed closely theoretical expectations, accounting for the influence of sample size and heritability of the trait. Prediction accuracies declined by 42% if full-sib DH lines were replaced by half-sib DH lines, but statistically significantly better results could be achieved if half-sib DH lines were available from both instead of only one parent of the validation population. Once both parents of the validation population were represented in the TS, including more crosses with a constant TS size did not increase accuracies. Unrelated crosses showing opposite linkage phases with the validation population resulted in negative or reduced prediction accuracies, if used alone or in combination with related families, respectively. We suggest identifying and excluding such crosses from the TS. Moreover, the observed variability among populations and traits suggests that these uncertainties must be taken into account in models optimizing the allocation of resources in GS.
| S-EPMC3664858 | biostudies-other
Project description:One of the most important applications of genomic selection in maize breeding is to predict and identify the best untested lines from biparental populations, when the training and validation sets are derived from the same cross. Nineteen tropical maize biparental populations evaluated in multienvironment trials were used in this study to assess prediction accuracy of different quantitative traits using low-density (~200 markers) and genotyping-by-sequencing (GBS) single-nucleotide polymorphisms (SNPs), respectively. An extension of the Genomic Best Linear Unbiased Predictor that incorporates genotype × environment (GE) interaction was used to predict genotypic values; cross-validation methods were applied to quantify prediction accuracy. Our results showed that: (1) low-density SNPs (~200 markers) were largely sufficient to get good prediction in biparental maize populations for simple traits with moderate-to-high heritability, but GBS outperformed low-density SNPs for complex traits and simple traits evaluated under stress conditions with low-to-moderate heritability; (2) heritability and genetic architecture of target traits affected prediction performance, prediction accuracy of complex traits (grain yield) were consistently lower than those of simple traits (anthesis date and plant height) and prediction accuracy under stress conditions was consistently lower and more variable than under well-watered conditions for all the target traits because of their poor heritability under stress conditions; and (3) the prediction accuracy of GE models was found to be superior to that of non-GE models for complex traits and marginal for simple traits.
| S-EPMC4815582 | biostudies-other