ProbBreed: a novel tool for calculating the risk of cultivar recommendation in multienvironment trials.

Neglecting genotype-by-environment interactions in multienvironment trials (MET) increases the risk of flawed cultivar recommendations for growers. Recent advancements in probability theory coupled with cutting-edge software offer a more streamlined decision-making process for selecting suitable candidates across diverse environments. Here, we present the user-friendly ProbBreed package in R, which allows breeders to calculate the probability of a given genotype outperforming competitors under a Bayesian framework. This article outlines the package's basic workflow and highlights its key features, ranging from MET model fitting to estimating the per se and pairwise probabilities of superior performance and stability for selection candidates. Remarkably, only the selection intensity is required to compute these probabilities. By democratizing this complex yet efficient methodology, ProbBreed aims to enhance decision-making and ultimately contribute to more accurate cultivar recommendations in breeding programs.

Leveraging probability concepts for cultivar recommendation in multi-environment trials.

KEY MESSAGE: We propose using probability concepts from Bayesian models to leverage a more informed decision-making process toward cultivar recommendation in multi-environment trials. Statistical models that capture the phenotypic plasticity of a genotype across environments are crucial in plant breeding programs to potentially identify parents, generate offspring, and obtain highly productive genotypes for target environments. In this study, our aim is to leverage concepts of Bayesian models and probability methods of stability analysis to untangle genotype-by-environment interaction (GEI). The proposed method employs the posterior distribution obtained with the No-U-Turn sampler algorithm to get Hamiltonian Monte Carlo estimates of adaptation and stability probabilities. We applied the proposed models in two empirical tropical datasets. Our findings provide a basis to enhance our ability to consider the uncertainty of cultivar recommendation for global or specific adaptation. We further demonstrate that probability methods of stability analysis in a Bayesian framework are a powerful tool for unraveling GEI given a defined intensity of selection that results in a more informed decision-making process toward cultivar recommendation in multi-environment trials.

Estimation of Molecular Pairwise Relatedness in Autopolyploid Crops.

A suitable pairwise relatedness estimation is key to genetic studies. Several methods are proposed to compute relatedness in autopolyploids based on molecular data. However, unlike diploids, autopolyploids still need further studies considering scenarios with many linked molecular markers with known dosage. In this study, we provide guidelines for plant geneticists and breeders to access trustworthy pairwise relatedness estimates. To this end, we simulated populations considering different ploidy levels, meiotic pairings patterns, number of loci and alleles, and inbreeding levels. Analysis were performed to access the accuracy of distinct methods and to demonstrate the usefulness of molecular marker in practical situations. Overall, our results suggest that at least 100 effective biallelic molecular markers are required to have good pairwise relatedness estimation if methods based on correlation is used. For this number of loci, current methods based on multiallelic markers show lower performance than biallelic ones. To estimate relatedness in cases of inbreeding or close relationships (as parent-offspring, full-sibs, or half-sibs) is more challenging. Methods to estimate pairwise relatedness based on molecular markers, for different ploidy levels or pedigrees were implemented in the AGHmatrix R package.

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.

Novel Bayesian Networks for Genomic Prediction of Developmental Traits in Biomass Sorghum.

The ability to connect genetic information between traits over time allow Bayesian networks to offer a powerful probabilistic framework to construct genomic prediction models. In this study, we phenotyped a diversity panel of 869 biomass sorghum (Sorghum bicolor (L.) Moench) lines, which had been genotyped with 100,435 SNP markers, for plant height (PH) with biweekly measurements from 30 to 120 days after planting (DAP) and for end-of-season dry biomass yield (DBY) in four environments. We evaluated five genomic prediction models: Bayesian network (BN), Pleiotropic Bayesian network (PBN), Dynamic Bayesian network (DBN), multi-trait GBLUP (MTr-GBLUP), and multi-time GBLUP (MTi-GBLUP) models. In fivefold cross-validation, prediction accuracies ranged from 0.46 (PBN) to 0.49 (MTr-GBLUP) for DBY and from 0.47 (DBN, DAP120) to 0.75 (MTi-GBLUP, DAP60) for PH. Forward-chaining cross-validation further improved prediction accuracies of the DBN, MTi-GBLUP and MTr-GBLUP models for PH (training slice: 30-45 DAP) by 36.4-52.4% relative to the BN and PBN models. Coincidence indices (target: biomass, secondary: PH) and a coincidence index based on lines (PH time series) showed that the ranking of lines by PH changed minimally after 45 DAP. These results suggest a two-level indirect selection method for PH at harvest (first-level target trait) and DBY (second-level target trait) could be conducted earlier in the season based on ranking of lines by PH at 45 DAP (secondary trait). With the advance of high-throughput phenotyping technologies, our proposed two-level indirect selection framework could be valuable for enhancing genetic gain per unit of time when selecting on developmental traits.

High-Resolution Genetic Map and QTL Analysis of Growth-Related Traits of Hevea brasiliensis Cultivated Under Suboptimal Temperature and Humidity Conditions.

Rubber tree (Hevea brasiliensis) cultivation is the main source of natural rubber worldwide and has been extended to areas with suboptimal climates and lengthy drought periods; this transition affects growth and latex production. High-density genetic maps with reliable markers support precise mapping of quantitative trait loci (QTL), which can help reveal the complex genome of the species, provide tools to enhance molecular breeding, and shorten the breeding cycle. In this study, QTL mapping of the stem diameter, tree height, and number of whorls was performed for a full-sibling population derived from a GT1 and RRIM701 cross. A total of 225 simple sequence repeats (SSRs) and 186 single-nucleotide polymorphism (SNP) markers were used to construct a base map with 18 linkage groups and to anchor 671 SNPs from genotyping by sequencing (GBS) to produce a very dense linkage map with small intervals between loci. The final map was composed of 1,079 markers, spanned 3,779.7 cM with an average marker density of 3.5 cM, and showed collinearity between markers from previous studies. Significant variation in phenotypic characteristics was found over a 59-month evaluation period with a total of 38 QTLs being identified through a composite interval mapping method. Linkage group 4 showed the greatest number of QTLs (7), with phenotypic explained values varying from 7.67 to 14.07%. Additionally, we estimated segregation patterns, dominance, and additive effects for each QTL. A total of 53 significant effects for stem diameter were observed, and these effects were mostly related to additivity in the GT1 clone. Associating accurate genome assemblies and genetic maps represents a promising strategy for identifying the genetic basis of phenotypic traits in rubber trees. Then, further research can benefit from the QTLs identified herein, providing a better understanding of the key determinant genes associated with growth of Hevea brasiliensis under limiting water conditions.

Linkage Disequilibrium and Population Structure in Wild and Cultivated Populations of Rubber Tree (Hevea brasiliensis).

Among rubber tree species, which belong to the Hevea genus of the Euphorbiaceae family, Hevea brasiliensis (Willd. ex Adr.de Juss.) Muell. Arg. is the main commercial source of natural rubber production worldwide. Knowledge of the population structure and linkage disequilibrium (LD) of this species is essential for the efficient organization and exploitation of genetic resources. Here, we obtained single-nucleotide polymorphisms (SNPs) using a genotyping-by-sequencing (GBS) approach and then employed the SNPs for the following objectives: (i) to identify the positions of SNPs on a genetic map of a segregating mapping population, (ii) to evaluate the population structure of a germplasm collection, and (iii) to detect patterns of LD decay among chromosomes for future genetic association studies in rubber tree. A total of 626 genotypes, including both germplasm accessions (368) and individuals from a genetic mapping population (254), were genotyped. A total of 77,660 and 21,283 SNPs were detected by GBS in the germplasm and mapping populations, respectively. The mapping population, which was previously mapped, was constructed with 1,062 markers, among which only 576 SNPs came from GBS, reducing the average interval between two adjacent markers to 4.4 cM. SNPs from GBS genotyping were used for the analysis of genetic structure and LD estimation in the germplasm accessions. Two groups, which largely corresponded to the cultivated and wild populations, were detected using STRUCTURE and via principal coordinate analysis. LD analysis, also using the mapped SNPs, revealed that non-random associations varied along chromosomes, with regions of high LD interspersed with regions of low LD. Considering the length of the genetic map (4,693 cM) and the mean LD (0.49 for cultivated and 0.02 for wild populations), a large number of evenly spaced SNPs would be needed to perform genome-wide association studies in rubber tree, and the wilder the genotypes used, the more difficult the mapping saturation.

Linking rhizosphere microbiome composition of wild and domesticated Phaseolus vulgaris to genotypic and root phenotypic traits.

Plant domestication was a pivotal accomplishment in human history, but also led to a reduction in genetic diversity of crop species compared to their wild ancestors. How this reduced genetic diversity affected plant-microbe interactions belowground is largely unknown. Here, we investigated the genetic relatedness, root phenotypic traits and rhizobacterial community composition of modern and wild accessions of common bean (Phaseolus vulgaris) grown in agricultural soil from the highlands of Colombia, one of the centers of common bean diversification. Diversity Array Technology-based genotyping and phenotyping of local common bean accessions showed significant genetic and root architectural differences between wild and modern accessions, with a higher specific root length for the wild accessions. Canonical Correspondence Analysis indicated that the divergence in rhizobacterial community composition between wild and modern bean accessions is associated with differences in specific root length. Along the bean genotypic trajectory, going from wild to modern, we observed a gradual decrease in relative abundance of Bacteroidetes, mainly Chitinophagaceae and Cytophagaceae, and an increase in relative abundance of Actinobacteria and Proteobacteria, in particular Nocardioidaceae and Rhizobiaceae, respectively. Collectively, these results establish a link between common bean domestication, specific root morphological traits and rhizobacterial community assembly.

AGHmatrix: R Package to Construct Relationship Matrices for Autotetraploid and Diploid Species: A Blueberry Example.

Progress in the rate of improvement in autopolyploid species has been limited compared with diploids, mainly because software and methods to apply advanced prediction and selection methodologies in autopolyploids are lacking. The objectives of this research were to (i) develop an R package for autopolyploids to construct the relationship matrix derived from pedigree information that accounts for autopolyploidy and double reduction and (ii) use the package to estimate the level and effect of double reduction in an autotetraploid blueberry breeding population with extensive pedigree information. The package is unique, as it can create A-matrices for different levels of ploidy and double reduction, which can then be used by breeders to fit mixed models in the context of predicting breeding values (BVs). Using the data from this blueberry population, we found for all the traits that tetrasomic inheritance creates a better fit than disomic inheritance. In one of the five traits studied, the level of double reduction was different from zero, decreasing the estimated heritability, but it did not affect the prediction of BVs. We also discovered that different depths of pedigree would have significant implications on the estimation of double reduction using this approach. This freely available R package is available for autopolyploid breeders to estimate the level of double reduction present in their populations and the impact in the estimation of genetic parameters as well as to use advanced methods of prediction and selection.

Evidence of Allopolyploidy in Urochloa humidicola Based on Cytological Analysis and Genetic Linkage Mapping.

The African species Urochloa humidicola (Rendle) Morrone & Zuloaga (syn. Brachiaria humidicola (Rendle) Schweick.) is an important perennial forage grass found throughout the tropics. This species is polyploid, ranging from tetra to nonaploid, and apomictic, which makes genetic studies challenging; therefore, the number of currently available genetic resources is limited. The genomic architecture and evolution of U. humidicola and the molecular markers linked to apomixis were investigated in a full-sib F1 population obtained by crossing the sexual accession H031 and the apomictic cultivar U. humidicola cv. BRS Tupi, both of which are hexaploid. A simple sequence repeat (SSR)-based linkage map was constructed for the species from 102 polymorphic and specific SSR markers based on simplex and double-simplex markers. The map consisted of 49 linkage groups (LGs) and had a total length of 1702.82 cM, with 89 microsatellite loci and an average map density of 10.6 cM. Eight homology groups (HGs) were formed, comprising 22 LGs, and the other LGs remained ungrouped. The locus that controls apospory (apo-locus) was mapped in LG02 and was located 19.4 cM from the locus Bh027.c.D2. In the cytological analyses of some hybrids, bi- to hexavalents at diakinesis were observed, as well as two nucleoli in some meiocytes, smaller chromosomes with preferential allocation within the first metaphase plate and asynchronous chromosome migration to the poles during anaphase. The linkage map and the meiocyte analyses confirm previous reports of hybridization and suggest an allopolyploid origin of the hexaploid U. humidicola. This is the first linkage map of an Urochloa species, and it will be useful for future quantitative trait locus (QTL) analysis after saturation of the map and for genome assembly and evolutionary studies in Urochloa spp. Moreover, the results of the apomixis mapping are consistent with previous reports and confirm the need for additional studies to search for a co-segregating marker.

SNP genotyping allows an in-depth characterisation of the genome of sugarcane and other complex autopolyploids.

Many plant species of great economic value (e.g., potato, wheat, cotton, and sugarcane) are polyploids. Despite the essential roles of autopolyploid plants in human activities, our genetic understanding of these species is still poor. Recent progress in instrumentation and biochemical manipulation has led to the accumulation of an incredible amount of genomic data. In this study, we demonstrate for the first time a successful genetic analysis in a highly polyploid genome (sugarcane) by the quantitative analysis of single-nucleotide polymorphism (SNP) allelic dosage and the application of a new data analysis framework. This study provides a better understanding of autopolyploid genomic structure and is a sound basis for genetic studies. The proposed methods can be employed to analyse the genome of any autopolyploid and will permit the future development of high-quality genetic maps to assist in the assembly of reference genome sequences for polyploid species.

Identification of QTLs associated with citrus resistance to Phytophthora gummosis.

Citrus gummosis, caused by Phytophthora spp., is an important citrus disease in Brazil. Almost all citrus rootstock varieties are susceptible to it to some degree, whereas resistance is present in Poncirus trifoliata, a closely related species. The objective of this study was to detect QTLs linked to citrus Phytophthora gummosis resistance. Eighty individuals of the F1 progeny, obtained by controlled crosses between Sunki mandarin Citrus sunki (susceptible) and Poncirus trifoliata cv. Rubidoux (resistant), were evaluated. Resistance to Phytophthora parasitica was evaluated by inoculating stems of young plants with a disc of fungal mycelia and measuring lesion lengths a month later. Two QTLs linked to gummosis resistance were detected in linkage groups 1 and 5 of the P. trifoliata map, and one QTL in linkage group 2 of the C. sunki map. The phenotypic variation explained by individual QTLs was 14% for C. sunki and ranged from 16 to 24% for P. trifoliata. The low character heritability (h2 = 18.7%) and the detection of more than one QTL associated with citrus Phytophthora gummosis resistance showed that inheritance of the resistance is quantitative.

Comparison of RAPD, RFLP, AFLP and SSR markers for diversity studies in tropical maize inbred lines

In order to compare their relative efficiencies as markers and to find the most suitable marker for maize diversity studies we evaluated 18 inbred tropical maize lines using a number of different loci as markers. The loci used were: 774 amplified fragment length polymorphisms (AFLPs); 262 random amplified polymorphic DNAs (RAPDs); 185 restriction fragment length polymorphisms (RFLPs); and 68 simple sequence repeats (SSR). For estimating genetic distance the AFLP and RFLP markers gave the most correlated results, with a correlation coefficient of r = 0.87. Bootstrap analysis were used to evaluate the number of loci for the markers and the coefficients of variation (CV) revealed a skewed distribution. The dominant markers (AFLP and RAPD) had small CV values indicating a skewed distribution while the codominant markers gave high CV values. The use of maximum values of genetic distance CVs within each sample size was efficient in determining the number of loci needed to obtain a maximum CV of 10 percent. The number of RFLP and AFLP loci used was enough to give CV values of below 5 percent, while the SSRs and RAPD loci gave higher CV values. Except for the RAPD markers, all the markers correlated genetic distance with single cross performance and heterosis which showed that they could be useful in predicting single cross performance and heterosis in intrapopulation crosses for broad-based populations. Our results indicate that AFLP seemed to be the best-suited molecular assay for fingerprinting and assessing genetic relationships among tropical maize inbred lines with high accuracy.