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At least 55 records · Page 3

Whole-Genome Comparisons of Ergot Fungi Reveals the Divergence and Evolution of Species within the Genus Claviceps Are the Result of Varying Mechanisms Driving Genome Evolution and Host Range Expansion

The genus Claviceps has been known for centuries as an economically important fungal genus for pharmacology and agricultural research. Only recently have researchers begun to unravel the evolutionary history of the genus, with origins in South America and classification of four distinct sections through ecological, morphological, and metabolic features (Claviceps sects. Citrinae, Paspalorum, Pusillae, and Claviceps). The first three sections are additionally characterized by narrow host range, whereas section Claviceps is considered evolutionarily more successful and adaptable as it has the largest host range and biogeographical distribution. However, the reasons for this success and adaptability remain unclear. Our study elucidates factors influencing adaptability by sequencing and annotating 50 Claviceps genomes, representing 21 species, for a comprehensive comparison of genome architecture and plasticity in relation to host range potential. Our results show the trajectory from specialized genomes (sects. Citrinae and Paspalorum) toward adaptive genomes (sects. Pusillae and Claviceps) through colocalization of transposable elements around predicted effectors and a putative loss of repeat-induced point mutation resulting in unconstrained tandem gene duplication coinciding with increased host range potential and speciation. Alterations of genomic architecture and plasticity can substantially influence and shape the evolutionary trajectory of fungal pathogens and their adaptability. Furthermore, our study provides a large increase in available genomic resources to propel future studies of Claviceps in pharmacology and agricultural research, as well as, research into deeper understanding of the evolution of adaptable plant pathogens.

59 BASIC BIOLOGICAL SCIENCES↗

Compilation and utilization of a sorghum transcriptome compendium for gene regulatory network analysis and crop trait engineering

Sorghum bicolor (Sorghum) is a drought and heat tolerant C4 grass crop used to produce grain, forage, biofuels, and other bioproducts. Genetic improvement of sorghum hybrid crops is aided by a large and diverse germplasm, sorghum's diploid inbreeding genetics, and a relatively small genome that has facilitated genomic research. Over the past 20 years, the sorghum research community characterized the cytogenetic and recombinant landscapes of sorghum's 10 chromosomes, sequenced and annotated the sorghum genome, and used that information to identify genes/alleles that modulate flowering time, plant height, seed shattering, and other important traits. More recently, >1000 RNA-seq transcriptome profiles were collected from 15 sorghum genotypes to help understand the genetic basis of variation in growth and development of sorghum stems, tillers, roots, and leaves, and the regulation of biosynthetic pathways that produce epicuticular wax, dhurrin, and RFOs, compounds that contribute to sorghum's resilience. Transcriptome studies were designed to identify differentially expressed genes that are co-expressed during development or in response to a treatment to enable construction of gene regulatory networks. Co-expression and network analysis identified transcription factors and their cognate binding sites in target gene promoters and signaling pathways that modulate gene regulatory networks providing gene editing targets for further trait optimization. RNA-seq data from >20 experiments targeting sorghum organs, tissues, cell types, developmental stages, and responses to environmental conditions (i.e., diel, day-length, shading, water-deficit, temperature) has been compiled in a sorghum transcriptome compendium. The goal of this resource paper is to describe compendium content, accessibility, and a compendium data analysis pipeline and to illustrate the types of information that can be derived from the compendium with a focus on the elucidation of gene regulatory networks useful for guiding the improvement of sorghum traits through gene editing.

RNA-seq↗

Inventory of Composable Elements (ICE) v6.0.0

The Inventory of Composable Elements (ICE) is an open source registry software platform for managing information about biological parts. It is capable of recording information about plasmids, microbial host strains and seeds, as well as DNA parts. Includes features such as DNA sequence visualization, editing and annotation, auto-aligning sequencing trace files against reference templates, SBOL XML/RDF support, and web-of-registries functionality. The web of registries functionality provides strong support for distributed interconnected use and enables sharing and transfer of biological parts across various independent ICE instances. ICE adopts modern software development principles, leveraging component-base frameworks, offering a REST API for convenient third-party integration and emphasizing scalability, security, and service integrations for dynamic content availability. The source code is hosted at https://github.com/JBEI/ice. A public instance is available at public-registry.jbei.org, where users can try out features, upload parts or simply use it for their projects.

Plahar, Hector↗

Physiological, genomic, and sulfur isotopic characterization of methanol metabolism by Desulfovibrio carbinolicus

Methanol is often considered as a non-competitive substrate for methanogenic archaea, but an increasing number of sulfate-reducing microorganisms (SRMs) have been reported to be capable of respiring with methanol as an electron donor. A better understanding of the fate of methanol in natural or artificial anaerobic systems thus requires knowledge of the methanol dissimilation by SRMs. In this study, we describe the growth kinetics and sulfur isotope effects of Desulfovibrio carbinolicus, a methanol-oxidizing sulfate-reducing deltaproteobacterium, together with its genome sequence and annotation. D. carbinolicus can grow with a series of alcohols from methanol to butanol. Compared to longer-chain alcohols, however, specific growth and respiration rates decrease by several fold with methanol as an electron donor. Larger sulfur isotope fractionation accompanies slowed growth kinetics, indicating low chemical potential at terminal reductive steps of respiration. In a medium containing both ethanol and methanol, D. carbinolicus does not consume methanol even after the cessation of growth on ethanol. Among the two known methanol dissimilatory systems, the genome of D. carbinolicus contains the genes coding for alcohol dehydrogenase but lacks enzymes analogous to methanol methyltransferase. We analyzed the genomes of 52 additional species of sulfate-reducing bacteria that have been tested for methanol oxidation. There is no apparent relationship between phylogeny and methanol metabolizing capacity, but most gram-negative methanol oxidizers grow poorly, and none carry homologs for methyltransferase (mtaB). Although the amount of available data is limited, it is notable that more than half of the known gram-positive methanol oxidizers have both enzymatic systems, showing enhanced growth relative to the SRMs containing only alcohol dehydrogenase genes. Thus, physiological, genomic, and sulfur isotopic results suggest that D. carbinolicus and close relatives have the ability to metabolize methanol but likely play a limited role in methanol degradation in most natural environments.

54 ENVIRONMENTAL SCIENCES↗

Energetics and Kinetics of Syntrophic Aromatic Degradation (Final Technical Report)

This DOE Basic Energy Physical Biosciences project spanned a 28-year period and two project investigators. Numerous significant research discoveries have occurred over this time frame. Much of this work has been reported in peer-reviewed literature, with the publication of results from the last four years forthcoming. The overarching project themes have focused on probing the metabolism of syntrophic bacteria and their environments. Research supported by this project has been central to ten doctoral dissertations and one master’s thesis at the University of Oklahoma. The project has also supported numerous undergraduate research projects throughout the years. Additionally, several microbial genomes were sequenced and annotated in association with this work 12-16. Key findings and publications from this work are highlighted. More detailed results are provided for unpublished and embargoed work. A complete list of publications and research products associated with this project is at the report's end.

59 BASIC BIOLOGICAL SCIENCES↗

KBase Narrative - StRoNG Net Part 2: Genome Analysis - Student - Static

Here we continue our exploration of novel genomes discovered in module 1. We will explore different approaches for examining the genome sequence and annotation data, investigating the best approaches for answering our question: Do benthic microbes have functioning circadian clocks?

Schirmer, Aaron↗

Draft genome of Rosenbergiella nectarea strain 8N4 T provides insights into the potential role of this species in its plant host

Background: Rosenbergiella nectarea strain 8N4 T , the type species of the genus Rosenbergiella, was isolated from Amygdalus communis (almond) floral nectar. Other strains of this species were isolated from the floral nectar of Citrus paradisi (grapefruit), Nicotiana glauca (tobacco tree) and from Asphodelus aestivus. R. nectarea strain 8N4 T is a Gram-negative, oxidase-negative, facultatively anaerobic bacterium in the family Enterobacteriaceae. Results: Here we describe features of this organism, together with its genome sequence and annotation. The DNA GC content is 47.38%, the assembly size is 3,294,717 bp, and the total number of genes are 3,346. The genome discloses the possible role that this species may play in the plant. The genome contains both virulence genes, like pectin lyase and hemolysin, that may harm plant cells and genes that are predicted to produce volatile compounds that may impact the visitation rates by nectar consumers, such as pollinators and nectar thieves. Conclusions: The genome of R. nectarea strain 8N4T reveals a mutualistic interaction with the plant host and a possible effect on plant pollination and fitness.

59 BASIC BIOLOGICAL SCIENCES↗

Sensitive and error-tolerant annotation of protein-coding DNA with BATH

We present BATH, a tool for highly sensitive annotation of protein-coding DNA based on direct alignment of that DNA to a database of protein sequences or profile hidden Markov models (pHMMs). BATH is built on top of the HMMER3 code base, and simplifies the annotation workflow for pHMM-based translated sequence annotation by providing a straightforward input interface and easy-to-interpret output. BATH also introduces novel frameshift-aware algorithms to detect frameshift-inducing nucleotide insertions and deletions (indels). BATH matches the accuracy of HMMER3 for annotation of sequences containing no errors, and produces superior accuracy to all tested tools for annotation of sequences containing nucleotide indels. These results suggest that BATH should be used when high annotation sensitivity is required, particularly when frameshift errors are expected to interrupt protein-coding regions, as is true with long-read sequencing data and in the context of pseudogenes.

59 BASIC BIOLOGICAL SCIENCES↗

Genome sequence, phylogenetic analysis, and structure-based annotation reveal metabolic potential of Chlorella sp. SLA-04

Algae are a broad class of photosynthetic eukaryotes that are phylogenetically and physiologically diverse. Most of the phylogenetic diversity has been inferred from 18S rDNA sequencing since there are only a few complete genomes available in public databases. Here we use ultra-long-read Nanopore sequencing to determine a gapless, telomere-to-telomere complete genome sequence of Chlorella sp. SLA-04, previously described as Chlorella sorokiniana SLA-04. Chlorella sp. SLA-04 is a green alga that grows to high cell density in a wide variety of environments - high and neutral pH, high and low alkalinity, and high and low salinity. SLA-04's ability to grow in high pH and high alkalinity media without external CO 2 supply is favorable for large-scale algal biomass production. Phylogenetic analysis performed using ribosomal DNA and conserved protein sequences consistently reveal that Chlorella sp. SLA-04 forms a distinct lineage from other strains of Chlorella sorokiniana. We complement traditional genome annotation methods with high throughput structural predictions and demonstrate that this approach expands functional prediction of the SLA-04 proteome. Genomic analysis of the SLA-04 genome identifies the genes capable of utilizing TCA cycle intermediates to replenish cytosolic acetyl-CoA pools for lipid production. We also identify a complete metabolic pathway for sphingolipid anabolism that may allow SLA-04 to readily adapt to changing environmental conditions and facilitate robust cultivation in mass production systems. Altogether, this work clarifies the phylogeny of Chlorella sp. SLA-04 within Trebouxiophyceae and demonstrates how structural predictions can be used to improve annotation beyond sequencebased methods.

59 BASIC BIOLOGICAL SCIENCES↗

A high-resolution single-molecule sequencing-based Arabidopsis transcriptome using novel methods of Iso-seq analysis

Accurate and comprehensive annotation of transcript sequences is essential for transcript quantification and differential gene and transcript expression analysis. Single-molecule long-read sequencing technologies provide improved integrity of transcript structures including alternative splicing, and transcription start and polyadenylation sites. However, accuracy is significantly affected by sequencing errors, mRNA degradation, or incomplete cDNA synthesis. We present a new and comprehensive Arabidopsis thaliana Reference Transcript Dataset 3 (AtRTD3). AtRTD3 contains over 169,000 transcripts—twice that of the best current Arabidopsis transcriptome and including over 1500 novel genes. Seventy-eight percent of transcripts are from Iso-seq with accurately defined splice junctions and transcription start and end sites. We develop novel methods to determine splice junctions and transcription start and end sites accurately. Mismatch profiles around splice junctions provide a powerful feature to distinguish correct splice junctions and remove false splice junctions. Stratified approaches identify high-confidence transcription start and end sites and remove fragmentary transcripts due to degradation. AtRTD3 is a major improvement over existing transcriptomes as demonstrated by analysis of an Arabidopsis cold response RNA-seq time-series. AtRTD3 provides higher resolution of transcript expression profiling and identifies cold-induced differential transcription start and polyadenylation site usage. AtRTD3 is the most comprehensive Arabidopsis transcriptome currently. It improves the precision of differential gene and transcript expression, differential alternative splicing, and transcription start/end site usage analysis from RNA-seq data. The novel methods for identifying accurate splice junctions and transcription start/end sites are widely applicable and will improve single-molecule sequencing analysis from any species.

transcription start and end sites↗

Galba: genome annotation with miniprot and AUGUSTUS

The Earth Biogenome Project has rapidly increased the number of available eukaryotic genomes, but most released genomes continue to lack annotation of protein-coding genes. In addition, no transcriptome data is available for some genomes. Various gene annotation tools have been developed but each has its limitations. Here, we introduce GALBA, a fully automated pipeline that utilizes miniprot, a rapid protein-to-genome aligner, in combination with AUGUSTUS to predict genes with high accuracy. Accuracy results indicate that GALBA is particularly strong in the annotation of large vertebrate genomes. We also present use cases in insects, vertebrates, and a land plant. GALBA is fully open source and available as a docker image for easy execution with Singularity in high-performance computing environments. Our pipeline addresses the critical need for accurate gene annotation in newly sequenced genomes, and we believe that GALBA will greatly facilitate genome annotation for diverse organisms.

59 BASIC BIOLOGICAL SCIENCES↗

Structural Models and Sequence Alignment Results of the Rhodospirillum rubrum Proteome

This dataset contains the structural models for the primary transcripts of the Rhodospirillum rubrum proteome as well as sequence alignment results for a subset of the encoded proteins. For each protein, the five models inferred from AlphaFold 2 are provided. The largest pTM-scoring model for each protein was energy minimized; this minimized structure as well as its AlphaFold pickle output file are also provided. This set of structures represent an alternate source of models for the R. rubrum proteome to those available in the AlphaFold Protein Structure Database. For proteins that have been annotated as hypothetical, sequence alignment results from the HHblits and SAdLSA alignment methods are provided. These methods are often more capable to resolve sequence homology than other methods. Therefore, the results from both HHblits and SAdLSA are provided to identify possible homologs for these challenging proteins. Numerous sequence databases are utilized for these alignments. References AlphaFold v2 Multimer: https://doi.org/10.1101/2021.10.04.463034. References HHBlits: https://doi.org/10.1186/s12859-019-3019-7. References SAdLSA: https://doi.org/10.3389/fbinf.2021.689960.

59 BASIC BIOLOGICAL SCIENCES↗

Protein remote homology detection and structural alignment using deep learning

Exploiting sequence–structure–function relationships in biotechnology requires improved methods for aligning proteins that have low sequence similarity to previously annotated proteins. We develop two deep learning methods to address this gap, TM-Vec and DeepBLAST. TM-Vec allows searching for structure–structure similarities in large sequence databases. It is trained to accurately predict TM-scores as a metric of structural similarity directly from sequence pairs without the need for intermediate computation or solution of structures. Once structurally similar proteins have been identified, DeepBLAST can structurally align proteins using only sequence information by identifying structurally homologous regions between proteins. It outperforms traditional sequence alignment methods and performs similarly to structure-based alignment methods. We show the merits of TM-Vec and DeepBLAST on a variety of datasets, including better identification of remotely homologous proteins compared with state-of-the-art sequence alignment and structure prediction methods.

59 BASIC BIOLOGICAL SCIENCES↗

The Thiamine-Pyrophosphate-Motif

Thiamin pyrophosphate (TPP), a derivative of vitamin B1, is a cofactor for enzymes performing catalysis in pathways of energy production including the well known decarboxylation of a-keto acid dehydrogenases followed by transketolation. TPP-dependent enzymes constitute a structurally and functionally diverse group exhibiting multimeric subunit organization, multiple domains and two chemically equivalent catalytic centers. Annotation of functional TPP-dependcnt enzymes, therefore, has not been trivial due to low sequence similarity related to this complex organization. Our approach to analysis of structures of known TPP-dependent enzymes reveals for the first time features common to this group, which we have termed the TPP-motif. The TPP-motif consists of specific spatial arrangements of structural elements and their specific contacts to provide for a flip-flop, or alternate site, enzymatic mechanism of action. Analysis of structural elements entrained in the flip-flop action displayed by TPP-dependent enzymes reveals a novel definition of the common amino acid sequences. These sequences allow for annotation of TPP-dependent enzymes, thus advancing functional proteomics. Further details of three-dimensional structures of TPP-dependent enzymes will be discussed.

Ciszak, Ewa↗

Accelerating Biological Insight for Understudied Genes

Synopsis The rapid expansion of genome sequence data is increasing the discovery of protein-coding genes across all domains of life. Annotating these genes with reliable functional information is necessary to understand evolution, to define the full biochemical space accessed by nature, and to identify target genes for biotechnology improvements. The majority of proteins are annotated based on sequence conservation with no specific biological, biochemical, genetic, or cellular function identified. Recent technical advances throughout the biological sciences enable experimental research on these understudied protein-coding genes in a broader collection of species. However, scientists have incentives and biases to continue focusing on well documented genes within their preferred model organism. This perspective suggests a research model that seeks to break historic silos of research bias by enabling interdisciplinary teams to accelerate biological functional annotation. We propose an initiative to develop coordinated projects of collaborating evolutionary biologists, cell biologists, geneticists, and biochemists that will focus on subsets of target genes in multiple model organisms. Concurrent analysis in multiple organisms takes advantage of evolutionary divergence and selection, which causes individual species to be better suited as experimental models for specific genes. Most importantly, multisystem approaches would encourage transdisciplinary critical thinking and hypothesis testing that is inherently slow in current biological research.

Zoology↗

MaizeMine: A Data Mining Warehouse for the Maize Genetics and Genomics Database

MaizeMine is the data mining resource of the Maize Genetics and Genome Database (MaizeGDB; http://maizemine.maizegdb.org). It enables researchers to create and export customized annotation datasets that can be merged with their own research data for use in downstream analyses. MaizeMine uses the InterMine data warehousing system to integrate genomic sequences and gene annotations from the Zea mays B73 RefGen_v3 and B73 RefGen_v4 genome assemblies, Gene Ontology annotations, single nucleotide polymorphisms, protein annotations, homologs, pathways, and precomputed gene expression levels based on RNA-seq data from the Z. mays B73 Gene Expression Atlas. MaizeMine also provides database cross references between genes of alternative gene sets from Gramene and NCBI RefSeq. MaizeMine includes several search tools, including a keyword search, built-in template queries with intuitive search menus, and a QueryBuilder tool for creating custom queries. The Genomic Regions search tool executes queries based on lists of genome coordinates, and supports both the B73 RefGen_v3 and B73 RefGen_v4 assemblies. The List tool allows you to upload identifiers to create custom lists, perform set operations such as unions and intersections, and execute template queries with lists. When used with gene identifiers, the List tool automatically provides gene set enrichment for Gene Ontology (GO) and pathways, with a choice of statistical parameters and background gene sets. With the ability to save query outputs as lists that can be input to new queries, MaizeMine provides limitless possibilities for data integration and meta-analysis.

59 BASIC BIOLOGICAL SCIENCES↗