Biology subjects

Doi, H.

Publications and source records attributed to Doi, H..

4 recordsLinked to original sources

bioRxiv2019

Spatial structures of fungal DNA assemblages revealed with eDNA metabarcoding in a forest river network in western Japan

Growing evidence has revealed high diversity and spatial heterogeneity of fungal communities including in local habitats in terrestrial ecosystems. These findings highlight the considerable sampling effort, analysis time, and costs required for the investigation of fungal diversity over large spatial scales. Recently, the analysis of environmental DNA in river water has been undertaken to study the biodiversity of organisms, such as animals and plants, in both aquatic and terrestrial habitats. However, previous studies have not investigated the spatial structure of fungal DNA assemblages in river water. In the present study, we investigate fungal DNA assemblages and their spatial structure using environmental DNA metabarcoding in water across different branches of river over forest landscapes. The river water was found to contain both phylogenetically and functionally diverse fungal DNA, including aquatic and terrestrial fungi, such as plant decomposers and mycorrhizal fungi. These fungal DNA assemblages were more similar within, rather than between, branches. In addition, the assemblages were more similar between spatially closer branches. These results imply that information on the terrestrial and aquatic fungal compositions of watersheds, and therefore their spatial structure can be obtained by investigating the fungal DNA assemblages in river water.

ecology↗

bioRxiv2019

Evaluation of biodiversity metrics through environmental DNA metabarcoding outperforms visual and capturing surveys

O_LIInformation on alpha (local), beta (between habitats), and gamma (regional) diversity is fundamental to understanding biodiversity as well as the function and stability of community dynamics. Methods like environmental DNA (eDNA) metabarcoding are currently considered useful to investigate biodiversity. C_LIO_LIWe compared the performance of eDNA metabarcoding with visual and capture surveys for estimating alpha and gamma diversity of river fish communities, and nestedness and turnover in particular. C_LIO_LIIn five rivers across west Japan, by comparison to visual/capture surveys, eDNA metabarcoding detected more species in the study sites (i.e., alpha diversity). Consequently the overall number of species in the region (i.e., gamma diversity) was higher. In particular, the species found by visual/capture surveys were encompassed by those detected by eDNA metabarcoding. C_LIO_LIEstimates of community diversity within rivers differed between survey methods. Although we found that the methods show similar levels of community nestedness and turnover within the rivers, visual/capture surveys showed more distinct community differences from upstream to downstream. Our results suggest that eDNA metabarcoding may be a suitable method for community assemblage analysis, especially for understanding regional community patterns, for fish monitoring in rivers. C_LI

ecology↗

bioRxiv2019

Biogeographic patterns of ectomycorrhizal fungal communities associated with Castanopsis sieboldii across the Japanese archipelago

Biogeographic patterns in ectomycorrhizal (ECM) fungal communities and their drivers have been elucidated, including effects of host tree species and abiotic (climatic and edaphic) conditions. At these geographic scales, genotypic diversity and composition of single host tree species change with spatial and environmental gradients, reflecting their historical dispersal events. However, whether the host genotypes can be associated with the biogeographic patterns of ECM communities remains unclear. We investigated the biogeographic pattern of ECM fungal community associated with the single host species Castanopsis sieboldii (Fagaceae), whose genotypic diversity and composition across the Japanese archipelago has already been evaluated, and we quantified the effect of host genotypes on the biogeographic pattern. Richness and community composition of ECM fungi changed with latitude and longitude; these biogeographic changes of ECM community were significantly explained by host genotypic variables. Quantitative analyses showed a higher relative explanatory power of climatic and spatial variables than that of host genotypic variables for the biogeographic patterns in the ECM community. Our results suggest the importance of historical events of host dispersal in determining the biogeographic patterns of the ECM fungal community, while their explanation power was lower than that for climatic filtering and/or fungal dispersal.

ecology↗

bioRxiv2019

Long-read sequencing identifies GGC repeat expansion in human-specific NOTCH2NLC associated with neuronal intranuclear inclusion disease

Neuronal intranuclear inclusion disease (NIID) is a progressive neurodegenerative disease characterized by eosinophilic hyaline intranuclear inclusions in neuronal and somatic cells. The wide range of clinical manifestations in NIID makes ante-mortem diagnosis difficult 1-8, but skin biopsy realized its ante-mortem diagnosis 9,10 and many NIID cases have been diagnosed by skin biopsy11,12. Most cases of NIID are sporadic, but several familial cases are known. Using a large NIID family, we conducted linkage mapping, found a 58.1-Mb linked-region at 1p22.1-q21.3 with a maximum logarithm of odds (LOD) score of 4.21, and successfully identified a GGC repeat expansion in the 5 portion of NOTCH2NLC in all affected members by long-read sequencing, but not in unaffected members. We further found the similar expansions in additional 8 unrelated families with NIID as well as 39 sporadic NIID patients. Repeat-primed PCR consistently detected the GGC repeat expansion in all the familial and sporadic patients diagnosed by skin biopsy, but never in unaffected family members nor 200 controls. This shows that pathogenic changes in a human-specific gene evolutionarily generated by segmental duplication indeed causes a human disease.

genetics↗