Statistical inference of selection and divergence of the rice blast resistance gene Pi-ta

Allelic variation in rice blast resistance: a pathway to sustainable disease management

Rice blast is a major problem in agriculture, affecting rice production and threatening food security worldwide. This disease, caused by the fungus Magnaporthe oryzae, has led to a lot of research since the discovery of the first resistance gene, pib, in 1999. Researchers have now identified more than 50 resistance genes on eight of the twelve chromosomes in rice, each targeting different strains of the pathogen.These genes are spread out across seventeen different loci. These genes, which primarily code for nucleotide-binding and leucine-rich repeat proteins, play an important part in the defense of rice against the pathogen, either alone or in combination with other genes. An important characteristic of these genes is the allelic or paralogous interactions that exist within these loci. These relationships contribute to the gene's increased capacity for evolutionary adaptation. The ability of resistance proteins to recognize and react to novel effectors is improved by the frequent occurrence of variations within the domains that are responsible for recognizing pathogen effectors. The purpose of this review is to summarize the progress that has been made in identifying these essential genes and to investigate the possibility of utilizing the allelic variants obtained from these genes in future rice breeding efforts to increase resistance to rice blast.

Retrospective research of rice blast development in Krasnodar region

Today, rice blast remains the most dangerous disease, therefore, along with breeding developments, it is necessary to study the dependence of the pathogen’s behavior on agroclimatic conditions. In addition, an understanding of the dynamics of blast development in the non-growing season is necessary. The studies conducted are aimed at establishing agroclimatic patterns that contribute to the development of the disease in the pre-growing and growing periods by analyzing the results of the implementation of the mathematical model. As a result of research, the dependence of the intensity of damage to rice crops on the intensity of environmental influences in the pre-growing season was established, which suggests that it is necessary to apply agrotechnological measures before sowing to reduce the phytosanitary load on plants and the environment.

Inferring the distribution of selective effects from a time inhomogeneous model

We have developed a Poisson random field model for estimating the distribution of selective effects of newly arisen nonsynonymous mutations that could be observed as polymorphism or divergence in samples of two related species under the assumption that the two species populations are not at mutation-selection-drift equilibrium. The model is applied to 91Drosophila genes by comparing levels of polymorphism in an African population of D. melanogaster with divergence to a reference strain of D. simulans. Based on the difference of gene expression level between testes and ovaries, the 91 genes were classified as 33 male-biased, 28 female-biased, and 30 sex-unbiased genes. Under a Bayesian framework, Markov chain Monte Carlo simulations are implemented to the model in which the distribution of selective effects is assumed to be Gaussian with a mean that may differ from one gene to the other to sample key parameters. Based on our estimates, the majority of newly-arisen nonsynonymous mutations that could contribute to polymorphism or divergence in Drosophila species are mildly deleterious with a mean scaled selection coefficient of -2.81, while almost 86% of the fixed differences between species are driven by positive selection. There are only 16.6% of the nonsynonymous mutations observed in sex-unbiased genes that are under positive selection in comparison to 30% of male-biased and 46% of female-biased genes that are beneficial. We also estimated that D. melanogaster and D. simulans may have diverged 1.72 million years ago.

Co-evolutionary interactions between host resistance and pathogen avirulence genes in rice-Magnaporthe oryzae pathosystem

Rice and Magnaporthe oryzae constitutes an ideal pathosystem for studying host-pathogen interaction in cereals crops. There are two alternative hypotheses, viz. Arms race and Trench warfare, which explain the co-evolutionary dynamics of hosts and pathogens which are under continuous confrontation. Arms race proposes that both R- and Avr- genes of host and pathogen, respectively, undergo positive selection. Alternatively, trench warfare suggests that either R- or Avr- gene in the pathosystem is under balanced selection intending to stabilize the genetic advantage gained over the opposition. Here, we made an attempt to test the above-stated hypotheses in rice-M. oryzae pathosystem at loci of three R-Avr gene pairs, Piz-t-AvrPiz-t, Pi54-AvrPi54 and Pita-AvrPita using allele mining approach. Allele mining is an efficient way to capture allelic variants existing in the population and to study the selective forces imposed on the variants during evolution. Results of nucleotide diversity, neutrality statistics and phylogenetic analyses reveal that Piz-t, Pi54 and AvrPita are diversified and under positive selection at their corresponding loci, while their counterparts, AvrPiz-t, AvrPi54 and Pita are conserved and under balancing selection, in nature. These results imply that rice-M. oryzae populations are engaged in a trench warfare at least at the three R/Avr loci studied. It is a maiden attempt to study the co-evolution of three R-Avr gene pairs in this pathosystem. Knowledge gained from this study will help in understanding the evolutionary dynamics of host-pathogen interaction in a better way and will also aid in developing new durable blast resistant rice varieties in future.