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Abstract Placing new sequences onto reference phylogenies is increasingly used for analyzing environmental samples, especially microbiomes. Existing placement methods assume that query sequences have evolved under specific models directly on the reference phylogeny. For example, they assume single-gene data (e.g., 16S rRNA amplicons) have evolved under the GTR model on a gene tree. Placement, however, often has a more ambitious goal: extending a (genome-wide) species tree given data from individual genes without knowing the evolutionary model. Addressing this challenging problem requires new directions. Here, we introduce Deep-learning Enabled Phylogenetic Placement (DEPP), an algorithm that learns to extend species trees using single genes without prespecified models. In simulations and on real data, we show that DEPP can match the accuracy of model-based methods without any prior knowledge of the model. We also show that DEPP can update the multilocus microbial tree-of-life with single genes with high accuracy. We further demonstrate that DEPP can combine 16S and metagenomic data onto a single tree, enabling community structure analyses that take advantage of both sources of data. [Deep learning; gene tree discordance; metagenomics; microbiome analyses; neural networks; phylogenetic placement.]
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Genome Sequencing of Paecilomyces Penicillatus Provides Insights into Its Phylogenetic Placement and Mycoparasitism Mechanisms on Morel Mushrooms
Morels (Morchella spp.) are popular edible fungi with significant economic and scientific value. However, white mold disease, caused by Paecilomyces penicillatus, can reduce morel yield by up to 80% in the main cultivation area in China. Paecilomyces is a polyphyletic genus and the exact phylogenetic placement of P. penicillatus is currently still unclear. Here, we obtained the first high-quality genome sequence of P. penicillatus generated through the single-molecule real-time (SMRT) sequencing platform. The assembled draft genome of P. penicillatus was 40.2 Mb, had an N50 value of 2.6 Mb and encoded 9454 genes. Phylogenetic analysis of single-copy orthologous genes revealed that P. penicillatus is in Hypocreales and closely related to Hypocreaceae, which includes several genera exhibiting a mycoparasitic lifestyle. CAZymes analysis demonstrated that P. penicillatus encodes a large number of fungal cell wall degradation enzymes. We identified many gene clusters involved in the production of secondary metabolites known to exhibit antifungal, antibacterial, or insecticidal activities. We further demonstrated through dual culture assays that P. penicillatus secretes certain soluble compounds that are inhibitory to the mycelial growth of Morchella sextelata. This study provides insights into the correct phylogenetic placement of P. penicillatus and the molecular mechanisms that underlie P. penicillatus pathogenesis.
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- Award ID(s):
- 1946445
- PAR ID:
- 10205674
- Date Published:
- Journal Name:
- Pathogens
- Volume:
- 9
- Issue:
- 10
- ISSN:
- 2076-0817
- Page Range / eLocation ID:
- 834
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.3390/pathogens9100834
