Evaluation of the ribosomal DNA internal transcribed spacer (ITS), specifically ITS1 and ITS2, for the analysis of fungal diversity by deep sequencing.

The nuclear ribosomal DNA internal transcribed spacer (ITS) has been widely used to assess the fungal composition in different environments by deep sequencing. To evaluate the ITS in the analysis of fungal diversity, comparisons of the clustering and taxonomy generated by sequencing with different portions of the whole fragment were conducted in this study. For a total of 83,120 full-length ITS sequences obtained from the UNITE database, it was found that, on average, ITS1 varied more than ITS2 within the kingdom Fungi; this variation included length and GC content variations and polymorphisms, with some polymorphisms specific to particular fungal groups. The taxonomic accuracy for ITS was higher than that for ITS1 or ITS2. The commonly used operational taxonomic unit (OTU) for evaluating fungal diversity and richness assigned several species to a single OTU even with clustering at 99.00% sequence similarity. The clustering and taxonomic capacities did not differ between ITS1 and ITS2. However, the OTU commonality between ITS1 and ITS2 was very low. To test this observation further, 219,741 pyrosequencing reads, including 39,840 full-length ITS sequences, were obtained from 10 soil samples and were clustered into OTUs. The pyrosequencing results agreed with the results of the in silico analysis. ITS1 might overestimate the fungal diversity and richness. Analyses using ITS, ITS1 and ITS2 yielded several different taxa, and the taxonomic preferences for ITS and ITS2 were similar. The results demonstrated that ITS2 alone might be a more suitable marker for revealing the operational taxonomic richness and taxonomy specifics of fungal communities when the full-length ITS is not available.

Modeling Habitat Suitability of Migratory Birds from Remote Sensing Images Using Convolutional Neural Networks.

With the application of various data acquisition devices, a large number of animal movement data can be used to label presence data in remote sensing images and predict species distribution. In this paper, a two-stage classification approach for combining movement data and moderate-resolution remote sensing images was proposed. First, we introduced a new density-based clustering method to identify stopovers from migratory birds’ movement data and generated classification samples based on the clustering result. We split the remote sensing images into 16 × 16 patches and labeled them as positive samples if they have overlap with stopovers. Second, a multi-convolution neural network model is proposed for extracting the features from temperature data and remote sensing images, respectively. Then a Support Vector Machines (SVM) model was used to combine the features together and predict classification results eventually. The experimental analysis was carried out on public Landsat 5 TM images and a GPS dataset was collected on 29 birds over three years. The results indicated that our proposed method outperforms the existing baseline methods and was able to achieve good performance in habitat suitability prediction.

Bacterial diversity in native habitats of the medicinal fungus Ophiocordyceps sinensis on Tibetan Plateau as determined using Illumina sequencing data.

Ophiocordyceps sinensis is one of the most well-known traditional Chinese medicinal fungi. In this study, bacterial diversity in the soils of native habitats of O. sinensis was investigated using Illumina sequencing data. A total of 525,000 sequences of V6-16S rRNA were analyzed. The number of OTUs from each sample ranged from 13,858 to 15,978 at 97% sequence similarity cut-off. The results demonstrated that the deep sequencing approach provides improved access to rare genotypes. Richness indices and Shannon's diversity index did not differ significantly between samples collected from locations where O. sinensis was present (Os1-3) and not present (NOs1-3). Classified bacterial sequences were grouped into 23 phyla including Proteobacteria, Actinobacteria, Acidobacteria, Verrucomicrobia, etc. The Venn diagram revealed that 7183 OTUs belonging to 14 phyla were shared by Os, NOs and MP (mycelial pellicle wrapping the sclerotium of O. sinensis) samples, possibly representing a core microbiome existing in native habitats of O. sinensis, and that 863 belonging to 12 phyla were shared by Os and MP samples, possibly related to the occurrence of O. sinensis. Overall, the results revealed a high bacterial diversity in the soil samples and the relationships between the bacterial diversity and O. sinensis merit further investigation.