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.

Repeat variants for the SbMATE transporter protect sorghum roots from aluminum toxicity by transcriptional interplay in cis and trans.

Acidic soils, where aluminum (Al) toxicity is a major agricultural constraint, are globally widespread and are prevalent in developing countries. In sorghum, the root citrate transporter SbMATE confers Al tolerance by protecting root apices from toxic Al3+, but can exhibit reduced expression when introgressed into different lines. We show that allele-specific SbMATE transactivation occurs and is caused by factors located away from SbMATE Using expression-QTL mapping and expression genome-wide association mapping, we establish that SbMATE transcription is controlled in a bipartite fashion, primarily in cis but also in trans Multiallelic promoter transactivation and ChIP analyses demonstrated that intermolecular effects on SbMATE expression arise from a WRKY and a zinc finger-DHHC transcription factor (TF) that bind to and trans-activate the SbMATE promoter. A haplotype analysis in sorghum RILs indicates that the TFs influence SbMATE expression and Al tolerance. Variation in SbMATE expression likely results from changes in tandemly repeated cis sequences flanking a transposable element (a miniature inverted repeat transposable element) insertion in the SbMATE promoter, which are recognized by the Al3+-responsive TFs. According to our model, repeat expansion in Al-tolerant genotypes increases TF recruitment and, hence, SbMATE expression, which is, in turn, lower in Al-sensitive genetic backgrounds as a result of lower TF expression and fewer binding sites. We thus show that even dominant cis regulation of an agronomically important gene can be subjected to precise intermolecular fine-tuning. These concerted cis/trans interactions, which allow the plant to sense and respond to environmental cues, such as Al3+ toxicity, can now be used to increase yields and food security on acidic soils.

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.