Epistasis and Quantitative Resistance to Pyricularia oryzae Revealed by GWAS in Advanced Rice Breeding Populations

Rice blast caused by Pyricularia oryzae is a major rice disease worldwide. Despite the detailed knowledge on major resistance genes available to date, little is known about how these genes interact with quantitative blast resistance loci and with the genetic background. Knowledge on these interactions is crucial for assessing the usefulness of introgressed resistance loci in breeding germplasm. Our goal was to identify quantitative trait loci (QTL) for blast resistance in rice breeding populations and to describe how they interact among each other and with the genetic background. To that end, resistance to blast was mapped by genome-wide association study (GWAS) in two advanced rice breeding subpopulations, one made of 305 indica type inbred lines, and the other of 245 tropical japonica inbred lines. The interactions and main effects of blast resistance loci were assessed in a multilocus model. Well known, major effect blast resistance gene clusters were detected in both tropical japonica (Pii/Pi3/Pi5) and indica (Piz/Pi2/Pi9) subpopulations with the GWAS scan 1. When these major effect loci were included as fixed cofactors in subsequent GWAS scans 2 and 3, additional QTL and more complex genetic architectures were revealed. The multilocus model for the tropical japonica subpopulation showed that Pii/Pi3/Pi5 had significant interaction with two QTL in chromosome 1 and one QTL in chromosome 8, together explaining 64% of the phenotypic variance. In the indica subpopulation a significant interaction among the QTL in chromosomes 6 and 4 and the genetic background, together with Piz/Pi2/Pi9 and QTL in chromosomes 1, 4 and 7, explained 35% of the phenotypic variance. Our results suggest that epistatic interactions can play a major role modulating the response mediated by major effect blast resistance loci such as Pii/Pi3/Pi5. Furthermore, the additive and epistatic effects of multiple QTL bring additional layers of quantitative resistance with a magnitude comparable to that of major effect loci. These findings highlight the need of genetic background-specific validation of markers for molecular assisted blast resistance breeding and provide insights for developing quantitative resistance to blast disease in rice.

Consequences of Single-Locus and Tightly Linked Genomic Architectures for Evolutionary Responses to Environmental Change

Genetic and genomic architectures of traits under selection are key factors influencing evolutionary responses. Yet, knowledge of their impacts has been limited by a widespread assumption that most traits are controlled by unlinked polygenic architectures. Recent advances in genome sequencing and eco-evolutionary modeling are unlocking the potential for integrating genomic information into predictions of population responses to environmental change. Using eco-evolutionary simulations, we demonstrate that hypothetical single-locus control of a life history trait produces highly variable and unpredictable harvesting-induced evolution relative to the classically applied multilocus model. Single-locus control of complex traits is thought to be uncommon, yet blocks of linked genes, such as those associated with some types of structural genomic variation, have emerged as taxonomically widespread phenomena. Inheritance of linked architectures resembles that of single loci, thus enabling single-locus-like modeling of polygenic adaptation. Yet, the number of loci, their effect sizes, and the degree of linkage among them all occur along a continuum. We review how linked architectures are often associated, directly or indirectly, with traits expected to be under selection from anthropogenic stressors and are likely to play a large role in adaptation to environmental disturbance. We suggest using single-locus models to explore evolutionary extremes and uncertainties when the trait architecture is unknown, refining parameters as genomic information becomes available, and explicitly incorporating linkage among loci when possible. By overestimating the complexity (e.g., number of independent loci) of the genomic architecture of traits under selection, we risk underestimating the complexity (e.g., nonlinearity) of their evolutionary dynamics.

Epistasis and Quantitative Resistance to Pyricularia oryzae Revealed by GWAS in Advanced Rice Breeding Populations

Background: Rice blast caused by Pyricularia oryzae is a major rice disease worldwide. Despite the detailed knowledge on major resistance genes available to date, little is known about how these genes interact with quantitative blast resistance loci and with the genetic background. Knowledge on these interactions is crucial for assessing the usefulness of introgressed resistance loci in breeding germplasm. Our goal was to identify blast resistance loci in rice breeding populations and to describe how they interact among each other and with the genetic background. To that end, resistance to blast was mapped in two advanced rice breeding populations, one made of 305 indica type inbred lines, and the other of 245 tropical japonica inbred lines. The interactions and main effects of blast resistance loci were assessed in a multilocus model. Results: Well known, major effect blast resistance gene clusters were detected in both tropical japonica (Pii/Pi3/Pi5) and indica (Piz/Pi2/Pi9) populations with the GWAS scan 1. When these major effect loci were included as fixed cofactors in subsequent GWAS scans 2 and 3, additional QTL and more complex genetic architectures were revealed. The multilocus model for the tropical japonica population showed that Pii/Pi3/Pi5 had significant interaction with two QTL in chromosome 1 and one QTL in chromosome 8, together explaining 64% of the phenotypic variance. In the indica population a significant interaction among the QTL in chromosomes 6 and 4 and the genetic background, together with Piz/Pi2/Pi9 and QTL in chromosomes 1, 4 and 7, explained 35% of the phenotypic variance.Conclusions: Our results suggest that epistatic interactions can play a major role modulating the effect of major effect blast resistance loci such as Pii/Pi3/Pi5. Furthermore, the additive and epistatic effects of multiple QTL bring additional layers of quantitative resistance with a magnitude comparable to that of major effect loci. These findings highlight the need of genetic background-specific validation of markers for molecular assisted blast resistance breeding and provide insights for developing quantitative resistance to blast disease in rice.

Weak epistasis may drive adaptation in recombining bacteria

The impact of epistasis on the evolution of multilocus traits depends on recombination. Population genetic theory has been largely developed for eukaryotes, many of which recombine so frequently that epistasis between polymorphisms has not been considered to play a large role in adaptation and has been compared to the fleeting influence of non-heritable effects. Many bacteria also recombine, some to the degree that their populations are described as 'panmictic' or 'freely recombining'. However, whether this recombination is sufficient to limit the ability of selection to act on epistatic contributions to fitness is unknown. We create a sensitive method to quantify homologous recombination in five bacterial pathogens and use these parameter estimates in a multilocus model of bacterial evolution with additive and epistatic effects. We find that even for highly recombining species (e.g. Streptococcus pneumoniae or Helicobacter pylori), selection may act on the cumulative effects of weak (as well as strong) interactions between distant mutations since homologous recombination typically transfers only short segments. Furthermore, whether selection acts more efficiently on physically proximal loci depends on the average recombination tract length. Epistasis may thus play an important role in the adaptive evolution of bacteria and, unlike in eukaryotes, does not need to be strong, involve near loci, or require specific metapopulation dynamics.

Outcrossing rate between 'Haden' and 'Tommy Atkins' mangoes estimated using microsatellite and AFLP markers

The objective of this work was to estimate outcrossing rates between Haden and Tommy Atkins mango cultivars, using AFLP and microsatellite markers. Progenies of an isolated 'Haden' plant, identified in a 'Tommy Atkins' commercial orchard, in Petrolina, PE, Brazil, were analyzed. Total DNA was isolated from the progeny leaves and used for AFLP and microsatellite reactions. Multilocus outcrossing rates (t m) were estimated by direct count of AFLP or microsatellite markers and by the mLTR software. Outcrossing rates ranged from 0.85 to 0.87 with the analysis based on seven AFLP markers, and from 0.83 to 0.91 based on three microsatellite primers. No unexpected band patterns were observed for 'Haden' and 'Tommy Atkins'. The estimates obtained with the mLTR software were close to those obtained by direct AFLP and microsatellite allele counting, which indicates that the multilocus model was appropriate for this kind of study. The microsatellites mMiCIR005, mMiCIR030, and mMiCIR036 can be used to elucidate the origin of 'Haden' and 'Tommy Atkins' seedlings.