Resolution of deep divergence of club fungi (phylum Basidiomycota)

Using PhyloSuite for molecular phylogeny and tree-based analyses

Phylogenetic analysis has entered the genomics (multilocus) era. For less experienced researchers, conquering the large number of software programs required for a multilocus-based phylogenetic reconstruction can be somewhat daunting and time-consuming. PhyloSuite, a software with a user-friendly GUI, was designed to make this process more accessible by integrating multiple software programs needed for multilocus and single-gene phylogenies and further streamlining the whole process. In this protocol, we aim to explain how to conduct each step of the phylogenetic pipeline and tree-based analyses in PhyloSuite. We also present a new version of PhyloSuite (v1.2.3), wherein we fixed some bugs, made some optimizations, and introduced some new functions, including a number of tree-based analyses, such as signal-to-noise calculation, saturation analysis, spurious species identification, and etc. The step-by-step protocol includes background information (i.e., what the step does), reasons (i.e., why do the step), and operations (i.e., how to do it). This protocol will help researchers quick-start their way through the multilocus phylogenetic analysis, especially those interested in conducting organelle-based analyses.

Kingdom-Wide Analysis of Fungal Transcriptomes and tRNAs Reveals Conserved Patterns of Adaptive Evolution

Protein-coding genes evolved codon usage bias due to the combined but uneven effects of adaptive and nonadaptive influences. Studies in model fungi agree on codon usage bias as an adaptation for fine-tuning gene expression levels; however, such knowledge is lacking for most other fungi. Our comparative genomics analysis of over 450 species supports codon usage and transfer RNAs (tRNAs) as coadapted for translation speed and this is most likely a realization of convergent evolution. Rather than drift, phylogenetic reconstruction inferred adaptive radiation as the best explanation for the variation of interspecific codon usage bias. Although the phylogenetic signals for individual codon and tRNAs frequencies are lower than expected by genetic drift, we found remarkable conservation of highly expressed genes being codon optimized for translation by the most abundant tRNAs, especially by inosine-modified tRNAs. As an application, we present a sequence-to-expression neural network that uses codons to reliably predict highly expressed transcripts. The kingdom Fungi, with over a million species, includes many key players in various ecosystems and good targets for biotechnology. Collectively, our results have implications for better understanding the evolutionary success of fungi, as well as informing the biosynthetic manipulation of fungal genes.

The Insights of Genomic Synteny and Codon Usage Preference on Genera Demarcation of Iridoviridae Family

The members of the family Iridoviridae are large, double-stranded DNA viruses that infect various hosts, including both vertebrates and invertebrates. Although great progress has been made in genomic and phylogenetic analyses, the adequacy of the existing criteria for classification within the Iridoviridae family remains unknown. In this study, we redetermined 23 Iridoviridae core genes by re-annotation, core-pan analysis and local BLASTN search. The phylogenetic tree based on the 23 re-annotated core genes (Maximum Likelihood, ML-Tree) and amino acid sequences (composition vector, CV-Tree) were found to be consistent with previous reports. Furthermore, the information provided by synteny analysis and codon usage preference (relative synonymous codon usage, correspondence analysis, ENC-plot and Neutrality plot) also supports the phylogenetic relationship. Collectively, our results will be conducive to understanding the genera demarcation within the Iridoviridae family based on genomic synteny and component (codon usage preference) and contribute to the existing taxonomy methods for the Iridoviridae family.

Toward a Fully Resolved Fungal Tree of Life

In this review, we discuss the current status and future challenges for fully elucidating the fungal tree of life. In the last 15 years, advances in genomic technologies have revolutionized fungal systematics, ushering the field into the phylogenomic era. This has made the unthinkable possible, namely access to the entire genetic record of all known extant taxa. We first review the current status of the fungal tree and highlight areas where additional effort will be required. We then review the analytical challenges imposed by the volume of data and discuss methods to recover the most accurate species tree given the sea of gene trees. Highly resolved and deeply sampled trees are being leveraged in novel ways to study fungal radiations, species delimitation, and metabolic evolution. Finally, we discuss the critical issue of incorporating the unnamed and uncultured dark matter taxa that represent the vast majority of fungal diversity.