Bika, R. | bioRxiv Science

bioRxiv2026

Evolution of supernumerary chromosomes in wheat blast fungal pathogens

A genome of Pyricularia oryzae (synonym Magnaporthe oryzae), the fungus that causes blast disease on diverse grass species, has seven core chromosomes and may contain supernumerary mini-chromosomes. The P. oryzae Triticum (PoT) pathotype is the phylogenetic lineage responsible for devastating epidemics of wheat blast disease. Genomic analysis of wheat blast field isolates from the initial outbreak in 1985 in Brazil through recent field isolates in South America revealed dynamic presence and structure of mini-chromosomes. Two "earliest" field isolates representing founder lineages for the Triticum pathotype contain similar mini-chromosomes. Another PoT founder isolate from 1986 and 37 out of 39 Triticum field isolates collected between 1986 and 1992 lack mini-chromosomes. Mini-chromosomes present in the founder strains each contain two copies of the PWT7 wheat blast avirulence gene, and PWT7 was lost from subsequent early strains through mini-chromosome loss. Almost all PoT field isolates from 2005 to 2020 have regained mini-chromosomes in which PWT7 sequences have been replaced by other sequences. Telomere-to-telomere assemblies of 11 mini-chromosomes identified two major mini-chromosome types in the South American PoT population, and demonstrated significant within-mini-chromosome sequence alterations as well as recombination with other mini-chromosomes or core chromosome ends. Additionally, our data indicate horizontal mini-chromosome transfer between Pyricularia species, resulting in nearly identical genomic fragments shared between P. oryzae and Pyricularia pennisetigena isolates in the PWT4 avirulence gene region. Our genomic analysis depicts the dynamic mini-chromosome compartment in the diverse South American Triticum field population through time, indicating important roles for mini-chromosomes in pathogen adaptation and pathogenicity.

evolutionary biology↗

bioRxiv2023

Using recurrent neural networks to detect supernumerary chromosomes in fungal strains causing blast diseases

The genomes of the fungus Magnaporthe oryzae that causes blast diseases on diverse grass species, including major crop plants, have indispensable core-chromosomes and may contain one or more additional supernumerary chromosomes, also known as mini-chromosomes. The mini-chromosome is speculated to play a role in fungal biology, provide effector gene mobility, and may transfer between strains. To understand and study the biological function of mini-chromosomes, it is crucial to be able to identify whether a given strain of M. oryzae possesses a mini-chromosome. In this study, we applied recurrent neural network models, more specifically, Bidirectional Long Short-Term Models (Bi-LSTM), for classifying DNA sequences as core-or mini-chromosomes. The models were trained with sequences from multiple available core- and mini-chromosome assemblies. The trained model was then used to predict the presence of the mini-chromosome in a global collection of M. oryzae isolates using short-read DNA sequences. The model predicted that the mini-chromosome was prevalent in M. oryzae isolates, including those isolated from rice, wheat, Lolium and many other grass species. Interestingly, 23 recent wheat strains collected since 2005 all carried the mini-chromosome, but none of nine early strains collected before 1991 had the mini-chromosome, indicating the preferential selection for strains carrying the mini-chromosome in recent years. Based on the limited sample size, we found the presence of the mini-chromosome in isolates of pathotype Eleusine was not as high as isolates of other pathotypes. The deep learning model was also used to identify assembled sequence contigs that were derived from the mini-chromosome and partial regions on core-chromosomes potentially translocated from a mini-chromosome. In summary, our study has developed a reliable method for categorizing DNA sequences and showcases an application of recurrent neural networks in the field of predictive genomics.

genomics↗