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1. Phylogenomics reveals extensive misidentification of fungal strains from the genus Aspergillus

   https://doi.org/10.1128/spectrum.03980-23  

   Steenwyk, Jacob L; Balamurugan, Charu; Raja, Huzefa A; Gonçalves, Carla; Li, Ningxiao; Martin, Frank; Berman, Judith; Oberlies, Nicholas H; Gibbons, John G; Goldman, Gustavo H; et al (April 2024, Microbiology Spectrum)

   Alanio, Alexandre (Ed.)

   ABSTRACT Modern taxonomic classification is often based on phylogenetic analyses of a few molecular markers, although single-gene studies are still common. Here, we leverage genome-scale molecular phylogenetics (phylogenomics) of species and populations to reconstruct evolutionary relationships in a dense data set of 710 fungal genomes from the biomedically and technologically important genusAspergillus. To do so, we generated a novel set of 1,362 high-quality molecular markers specific forAspergillusand provided profile Hidden Markov Models for each, facilitating their use by others. Examining the resulting phylogeny helped resolve ongoing taxonomic controversies, identified new ones, and revealed extensive strain misidentification (7.59% of strains were previously misidentified), underscoring the importance of population-level sampling in species classification. These findings were corroborated using the current standard, taxonomically informative loci. These findings suggest that phylogenomics of species and populations can facilitate accurate taxonomic classifications and reconstructions of the Tree of Life.IMPORTANCEIdentification of fungal species relies on the use of molecular markers. Advances in genomic technologies have made it possible to sequence the genome of any fungal strain, making it possible to use genomic data for the accurate assignment of strains to fungal species (and for the discovery of new ones). We examined the usefulness and current limitations of genomic data using a large data set of 710 publicly available genomes from multiple strains and species of the biomedically, agriculturally, and industrially important genusAspergillus. Our evolutionary genomic analyses revealed that nearly 8% of publicly availableAspergillusgenomes are misidentified. Our work highlights the usefulness of genomic data for fungal systematic biology and suggests that systematic genome sequencing of multiple strains, including reference strains (e.g., type strains), of fungal species will be required to reduce misidentification errors in public databases. 

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2. The Sordariomycetes: an expanding resource with Big Data for mining in evolutionary genomics and transcriptomics

   https://doi.org/10.3389/ffunb.2023.1214537  

   Wang, Zheng; Kim, Wonyong; Wang, Yen-Wen; Yakubovich, Elizabeta; Dong, Caihong; Trail, Frances; Townsend, Jeffrey P.; Yarden, Oded (June 2023, Frontiers in Fungal Biology)

   Advances in genomics and transcriptomics accompanying the rapid accumulation of omics data have provided new tools that have transformed and expanded the traditional concepts of model fungi. Evolutionary genomics and transcriptomics have flourished with the use of classical and newer fungal models that facilitate the study of diverse topics encompassing fungal biology and development. Technological advances have also created the opportunity to obtain and mine large datasets. One such continuously growing dataset is that of the Sordariomycetes, which exhibit a richness of species, ecological diversity, economic importance, and a profound research history on amenable models. Currently, 3,574 species of this class have been sequenced, comprising nearly one-third of the available ascomycete genomes. Among these genomes, multiple representatives of the model genera Fusarium , Neurospora , and Trichoderma are present. In this review, we examine recently published studies and data on the Sordariomycetes that have contributed novel insights to the field of fungal evolution via integrative analyses of the genetic, pathogenic, and other biological characteristics of the fungi. Some of these studies applied ancestral state analysis of gene expression among divergent lineages to infer regulatory network models, identify key genetic elements in fungal sexual development, and investigate the regulation of conidial germination and secondary metabolism. Such multispecies investigations address challenges in the study of fungal evolutionary genomics derived from studies that are often based on limited model genomes and that primarily focus on the aspects of biology driven by knowledge drawn from a few model species. Rapidly accumulating information and expanding capabilities for systems biological analysis of Big Data are setting the stage for the expansion of the concept of model systems from unitary taxonomic species/genera to inclusive clusters of well-studied models that can facilitate both the in-depth study of specific lineages and also investigation of trait diversity across lineages. The Sordariomycetes class, in particular, offers abundant omics data and a large and active global research community. As such, the Sordariomycetes can form a core omics clade, providing a blueprint for the expansion of our knowledge of evolution at the genomic scale in the exciting era of Big Data and artificial intelligence, and serving as a reference for the future analysis of different taxonomic levels within the fungal kingdom. 

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3. Fungal Genomes and Insights into the Evolution of the Kingdom.

   https://doi.org/10.1128/microbiolspec.FUNK-0055-2016  

   Stajich, Jason E (August 2017, Microbiology spectrum)

   The kingdom Fungi comprises species that inhabit nearly all ecosystems. Fungi exist as both free-living and symbiotic unicellular and multicellular organisms with diverse morphologies. The genomes of fungi encode genes that enable them to thrive in diverse environments, invade plant and animal cells, and participate in nutrient cycling in terrestrial and aquatic ecosystems. The continuously expanding databases of fungal genome sequences have been generated by individual and large-scale efforts such as Génolevures, Broad Institute's Fungal Genome Initiative, and the 1000 Fungal Genomes Project (http://1000.fungalgenomes.org). These efforts have produced a catalog of fungal genes and genomic organization. The genomic datasets can be utilized to better understand how fungi have adapted to their lifestyles and ecological niches. Large datasets of fungal genomic and transcriptomic data have enabled the use of novel methodologies and improved the study of fungal evolution from a molecular sequence perspective. Combined with microscopes, petri dishes, and woodland forays, genome sequencing supports bioinformatics and comparative genomics approaches as important tools in the study of the biology and evolution of fungi. 

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4. How Scalable Are Clade-Specific Marker K-Mer Based Hash Methods for Metagenomic Taxonomic Classification?

   https://doi.org/10.3389/frsip.2022.842513  

   Gray, Melissa; Zhao, Zhengqiao; Rosen, Gail L. (July 2022, Frontiers in Signal Processing)

   Efficiently and accurately identifying which microbes are present in a biological sample is important to medicine and biology. For example, in medicine, microbe identification allows doctors to better diagnose diseases. Two questions are essential to metagenomic analysis (the analysis of a random sampling of DNA in a patient/environment sample): How to accurately identify the microbes in samples and how to efficiently update the taxonomic classifier as new microbe genomes are sequenced and added to the reference database. To investigate how classifiers change as they train on more knowledge, we made sub-databases composed of genomes that existed in past years that served as “snapshots in time” (1999–2020) of the NCBI reference genome database. We evaluated two classification methods, Kraken 2 and CLARK with these snapshots using a real, experimental metagenomic sample from a human gut. This allowed us to measure how much of a real sample could confidently classify using these methods and as the database grows. Despite not knowing the ground truth, we could measure the concordance between methods and between years of the database within each method using a Bray-Curtis distance. In addition, we also recorded the training times of the classifiers for each snapshot. For all data for Kraken 2, we observed that as more genomes were added, more microbes from the sample were classified. CLARK had a similar trend, but in the final year, this trend reversed with the microbial variation and less unique k-mers. Also, both classifiers, while having different ways of training, generally are linear in time - but Kraken 2 has a significantly lower slope in scaling to more data. 

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5. Towards complete and error-free genome assemblies of all vertebrate species

   https://doi.org/10.1038/s41586-021-03451-0  

   Rhie, Arang; McCarthy, Shane A.; Fedrigo, Olivier; Damas, Joana; Formenti, Giulio; Koren, Sergey; Uliano-Silva, Marcela; Chow, William; Fungtammasan, Arkarachai; Kim, Juwan; et al (April 2021, Nature)

   null (Ed.)

   Abstract High-quality and complete reference genome assemblies are fundamental for the application of genomics to biology, disease, and biodiversity conservation. However, such assemblies are available for only a few non-microbial species 1–4 . To address this issue, the international Genome 10K (G10K) consortium 5,6 has worked over a five-year period to evaluate and develop cost-effective methods for assembling highly accurate and nearly complete reference genomes. Here we present lessons learned from generating assemblies for 16 species that represent six major vertebrate lineages. We confirm that long-read sequencing technologies are essential for maximizing genome quality, and that unresolved complex repeats and haplotype heterozygosity are major sources of assembly error when not handled correctly. Our assemblies correct substantial errors, add missing sequence in some of the best historical reference genomes, and reveal biological discoveries. These include the identification of many false gene duplications, increases in gene sizes, chromosome rearrangements that are specific to lineages, a repeated independent chromosome breakpoint in bat genomes, and a canonical GC-rich pattern in protein-coding genes and their regulatory regions. Adopting these lessons, we have embarked on the Vertebrate Genomes Project (VGP), an international effort to generate high-quality, complete reference genomes for all of the roughly 70,000 extant vertebrate species and to help to enable a new era of discovery across the life sciences. 

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