Shunsuke Nozawa

The genus Lasiodiplodia includes numerous plant-pathogenic species whose delimitation is complicated by overlapping morphological traits and limited resolution of common genetic markers. Lasiodiplodia brasiliensis was described as a species closely related to L. theobromae; however, its taxonomic status remains controversial. In this study, we re-evaluated the species boundaries between L. theobromae and L. brasiliensis using an integrative approach that combined multilocus and genome-scale phylogenetic analyses with morphological comparisons. Multilocus phylogenetic analyses based on ITS, tef1-α, tub2, and rpb2 revealed an unresolved relationship between the two taxa. The L. theobromae clade had low bootstrap support, whereas the ancestral node connecting both species had high support. In contrast, genome-scale phylogenetic analysis using hundreds of single-copy orthologous genes strongly supported a single monophyletic clade encompassing isolates assigned to both L. theobromae and L. brasiliensis. Morphological analyses further revealed that conidial dimensions and other diagnostic characteristics largely overlapped between the two taxa, rendering them unreliable criteria for species separation. Considering the combined molecular and morphological evidence, our results support treating L. brasiliensis as a synonym of L. theobromae. Clarifying species boundaries within this group helps stabilize the taxonomy of Lasiodiplodia and provides a reliable foundation for accurate pathogen identification and disease management.

Banana leaf diseases are a significant threat to Cavendish banana production. In the Philippines, the main disease has been diagnosed as Black sigatoka disease caused by Pseudocercospora fijiensis based on symptoms. However, our study showed that the main pathogen in Mindanao island, the largest banana-producing region in the Philippines, belongs to the genus Nigrospora, contradicting previous assumptions. We clarified the phylogenetic positions of 160 Nigrospora isolates based on molecular phylogenetic analyses using ITS, β-tubulin, and tef1α sequences, and compared their morphology with known species. Molecular phylogenetic and morphological analysis revealed that Nigrospora isolates comprised N. chinensis, N. lacticolonia, N. cf. singularis, N. sphaerica, N. vesicularifera, and a novel species, N. nigrocolonia. Pathogenicity tests on banana leaves confirmed that these species are pathogenic. Species other than N. sphaerica were for the first time reported as pathogens of banana leaf. The results of the fungicide sensitivity test using 14 fungicides, including pyrimethanil, spiroxamine, and tebuconazole, for the Sigatoka disease showed 100% inhibition of all isolates at 100 ppm of active ingredients. However, low-sensitivity isolates were observed for the remaining 11 fungicides. Our findings indicated the need for a comprehensive review of banana leaf disease prevention strategies.

Recent advances in high-throughput sequencing technologies have significantly enhanced the accuracy of phylogenetic inference, enabling comprehensive genome-wide analyses. Fusarium fungi, which include numerous agriculturally and medically important species, are typically classified at the species complex (SC) level. Clarifying the evolutionary relationships and distinctiveness of these SCs is therefore essential for accurate identification and understanding of their biology. Recent large-scale phylogenetic studies based on genomic data have provided a more resolved understanding of the evolutionary relationships among Fusarium SCs, supporting the view that most represent evolutionarily coherent and stable lineages. However, the phylogenetic position of Fusarium commune has not been explicitly examined, despite incongruence between phylogenies inferred from nucleotide and amino acid sequence data. This study aimed to clarify the phylogenetic placement of F. commune at the SC level by re-examining its position using a genome dataset independent of those employed in previous studies. Our results are largely consistent with previously reported genome-scale phylogenetic analyses of the genus Fusarium and support the stability of most SCs. However, F. commune was not clearly included in any of the currently recognized SCs and instead formed an independent lineage. These findings provide insights into the evolutionary history of Fusarium SCs and contribute to a better understanding of the taxonomic position of F. commune.

Recent developments in next-generation sequencing have improved the reliability of phylogenetic trees, allowing genome-wide phylogenetic analyses. Fusarium fungi are important phytopathogenic and clinical fungi. As the identification of species in this genus is conducted on a species complex (SC) basis, evaluating the monophyly of each SC and its evolutionary history are important. Recently, genome-scale phylogenetic analyses using a concatenation approach based on DNA data identified the putative phylogeny of Fusarium SCs. However, different data types and analytical approaches often yield different trees, and the possibility of alternative phylogenetic relationships has not yet been discussed. In this study, phylogenetic analyses using concatenation and coalescence approaches as well as polytomy tests based on DNA and amino acid data from 1,190 genes were performed on 23 Fusarium SCs. Our results suggest that (i) F. commune is independent of F. nisikadoi SC; (ii) the branching order among F. oxysporum SC, F. newnwsense SC, and F. nisikadoi SC cannot be determined; and (iii) the phylogenetic position of F. buxicola is inconsistent among the analyses. This study provides novel insights into the evolutionary history of Fusarium SCs and has implications for their classification and identification.

Fungal identification is based on sequence similarity comparisons, with multiple genes often utilized in conjunction, similar to most taxonomic studies. The identification process involves the individual comparison of the similarities of each gene. However, owing to insufficient information, incomplete lineage sorting, gene transfer, hybridization, gene duplication, and loss, different species may match, depending on the DNA region used for comparison. Additionally, identification methods exist that set a uniform similarity threshold value, but they hit multiple species above the threshold. In this study, we introduced ANI-netID, which was developed to address these challenges. ANI-netID is an identification method based on the phylogenetic species concept, where the threshold value is determined by the combination of individuals with the lowest nucleotide similarity within groups (clique groups), such as species and genera. This checks whether the queried individual fall into the same clique group as the reference individual with the highest similarity. ANI-netID solves not only the above-mentioned problems but also indicates that the individual being identified may represent a new lineage, if the individual does not belong to any clique group.