Search NASA⌕ Search

SEARCH · Search NASA

Results for “sequencing data annotation”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
NASA NTRS2003

An in silico assessment of gene function and organization of the phenylpropanoid pathway metabolic networks in Arabidopsis thaliana and limitations thereof

The Arabidopsis genome sequencing in 2000 gave to science the first blueprint of a vascular plant. Its successful completion also prompted the US National Science Foundation to launch the Arabidopsis 2010 initiative, the goal of which is to identify the function of each gene by 2010. In this study, an exhaustive analysis of The Institute for Genomic Research (TIGR) and The Arabidopsis Information Resource (TAIR) databases, together with all currently compiled EST sequence data, was carried out in order to determine to what extent the various metabolic networks from phenylalanine ammonia lyase (PAL) to the monolignols were organized and/or could be predicted. In these databases, there are some 65 genes which have been annotated as encoding putative enzymatic steps in monolignol biosynthesis, although many of them have only very low homology to monolignol pathway genes of known function in other plant systems. Our detailed analysis revealed that presently only 13 genes (two PALs, a cinnamate-4-hydroxylase, a p-coumarate-3-hydroxylase, a ferulate-5-hydroxylase, three 4-coumarate-CoA ligases, a cinnamic acid O-methyl transferase, two cinnamoyl-CoA reductases) and two cinnamyl alcohol dehydrogenases can be classified as having a bona fide (definitive) function; the remaining 52 genes currently have undetermined physiological roles. The EST database entries for this particular set of genes also provided little new insight into how the monolignol pathway was organized in the different tissues and organs, this being perhaps a consequence of both limitations in how tissue samples were collected and in the incomplete nature of the EST collections. This analysis thus underscores the fact that even with genomic sequencing, presumed to provide the entire suite of putative genes in the monolignol-forming pathway, a very large effort needs to be conducted to establish actual catalytic roles (including enzyme versatility), as well as the physiological function(s) for each member of the (multi)gene families present and the metabolic networks that are operative. Additionally, one key to identifying physiological functions for many of these (and other) unknown genes, and their corresponding metabolic networks, awaits the development of technologies to comprehensively study molecular processes at the single cell level in particular tissues and organs, in order to establish the actual metabolic context.

NASA Program Fundamental Space Biology↗
DOE OSTI2026

Finding the missing pieces: filling gaps that impede the translation of omics data into models

High-throughput omics technologies such as DNA sequencing have made the sequencing and computational assembly of microbial genomes recovered from the environment relatively routine. Computational inference of the protein products encoded by these genomes, and the associated biochemical functions, should enable the accurate prediction and modeling of microbial metabolism, organismal interactions, and ecosystem processes. However, a lack of scalable, probabilistic protein annotation tools limits the full potential of modeling for understanding the metabolism and biogeochemical cycles of microbial communities. Our approach to improve inference of protein annotations and metabolic models relied on learning from and emulating expert manual curation, leveraging software engineering and data science best practices to scale up the throughput and accuracy of annotations and metabolic model construction, building software to objectively evaluate different annotation strategies, and more closely linking the protein annotation and metabolic model inference process. Outcomes of this research include several improved or new computational tools, including DRAM (Distilled and Refined Annotation of Metabolism) for annotating microbial genomes with protein function and metabolic traits, CAMPER (Curated Annotations for Microbial Polyphenol Enzymes and Reactions) for annotating key polyphenol metabolisms, EC-Bench for comprehensive and unbiased benchmarking of annotation tools, and several apps available via the DOE Systems Biology Knowledgebase (KBase) for building genome-scale metabolic models. We demonstrate that these tools allow us to scalably annotate and understand thousands of genomes for microbial communities from a variety of systems and test cases, including rivers, thawing permafrost, and gut microbiomes. All of these computational tools are available as open-source software, with most broadly and easily accessible to the scientific community via KBase apps.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Genomes_SET2_178 - Shared

The dataset consists of 178 bacterial genomes in total. Of these, 145 genomes were drawn from published literature linked to Biolog Gen III growth data, while 33 genomes came from soil isolates collected at the Cedar Creek Ecosystem Science Research Reserve (CCESR) in Minnesota. The isolates were sequenced on an Illumina HiSeq platform (~50× coverage), assembled with Megahit, and annotated using RAST at PATRIC, with strict quality filtering (<90% completeness or >5% contamination).

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

TracKlinic: Diagnosis of Challenge Factors in Visual Tracking

Generic visual object tracking is difficult due to many challenge factors (e.g., occlusion, blur, etc.). Each of these factors may cause serious problems for a tracker, and when they work together can make things even more complicated. Despite a great amount of efforts devoted to understanding the behavior of trackers, reliable and quantifiable ways for studying the per factor tracking behavior remain barely available. Addressing this issue, in this paper we contribute to the community a tracking diagnosis toolkit, TracKlinic, for diagnosis of challenge factors of tracking algorithms. TracKlinic consists of two novel components focusing on the data and analysis aspects, respectively. For the data component, we carefully prepare a set of 2,390 annotated videos, each involving one and only one major challenge factor. When analyzing an algorithm for a specific challenge factor, such one-factor-per-sequence rule greatly inhibits the disturbance from other factors and consequently leads to more faithful analysis. For the analysis component, given the tracking results on all sequences, it investigates the behavior of the tracker under each individual factor and generates the report automatically. With TracKlinic, a thorough study is conducted on ten state-of-the-art trackers on nine challenge factors (including two compound ones). The results suggest that, heavy shape variation and occlusion are the two most challenging factors faced by most trackers. Besides, out-of-view, though does not happen frequently, is often fatal. By sharing TracKlinic1, we expect to make it much easier for diagnosing tracking algorithms, and to thus facilitate developing better ones.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Analysis of genomic signatures associated with Variovorax endosphere colonization

This repository contains the analysis code and supporting datasets associated with the study “Genomic signatures in Variovorax enabling colonization of the Populus endosphere.” Beals DG, Carper DL, Hochanadel LH, Jawdy SS, Klingeman DM, Piatkowski BT, Weston DJ, Doktycz MJ, Pelletier DA. 2026. Genomic signatures in Variovorax enabling colonization of the Populus endosphere. mSystems 11:e01605-25. https://doi.org/10.1128/msystems.01605-25 The scripts are organized sequentially (01–07) and document the workflows used for: Sequence-read alignment and feature counting Orthogroup and KEGG Ortholog annotation Count normalization Statistical analysis and aggregation Generation of manuscript figures and tables Repository contents The uncompressed files are the finalized, formatted datasets used to generate the figures and tables reported in the study, including the supplemental CSV files referenced in the manuscript. The accompanying ZIP archive contains the complete codebase and example data_input/ and data_output/ directories illustrating the organization and execution of the analytical workflow. Individual scripts identify the corresponding manuscript analyses and figure panels. Raw sequencing data Raw sequencing reads are available through the NCBI Sequence Read Archive under BioProject accession PRJNA1322484.

Beals, Delaney [ORNL] (ORCID:0000000306274574)↗
DOE OSTI2022

An optimized ChIP-Seq framework for profiling histone modifications in Chromochloris zofingiensis

The eukaryotic green alga Chromochloris zofingiensis is a reference organism for studying carbon partitioning and a promising candidate for the production of biofuel precursors. Recent transcriptome profiling transformed our understanding of its biology and generally algal biology, but epigenetic regulation remains understudied and represents a fundamental gap in our understanding of algal gene expression. Chromatin immunoprecipitation followed by deep sequencing (ChIP-Seq) is a powerful tool for the discovery of such mechanisms, by identifying genome-wide histone modification patterns and transcription factor-binding sites alike. Here, we established a ChIP-Seq framework for Chr. zofingiensis yielding over 20 million high-quality reads per sample. The most critical steps in a ChIP experiment were optimized, including DNA shearing to obtain an average DNA fragment size of 250 bp and assessment of the recommended formaldehyde concentration for optimal DNA-protein cross-linking. We used this ChIP-Seq framework to generate a genome-wide map of the H3K4me3 distribution pattern and to integrate these data with matching RNA-Seq data. In line with observations from other organisms, H3K4me3 marks predominantly transcription start sites of genes. Our H3K4me3 ChIP-Seq data will pave the way for improved genome structural annotation in the emerging reference alga Chr. zofingiensis.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1990

GENEX: A knowledge-based expert assistant for Genbank data analysis

We describe a knowledge-based expert assistant, GENEX (Gene Explorer), that simplifies some analysis of Genbank data. GENEX is written in CLIPS (C Language Integrated Production System), and expert system tool, developed at the NASA Johnson Space Center. The main purpose of the system is to look for gene start site annotations, unusual DNA sequence composition, and regulatory protein patterns. application where determinations are made via a decision tree.

Batra, Sajeev↗
DOE OSTI2020

Thaumarchaea Genome Sequences from a High Arctic Active Layer

The role of archaeal ammonia oxidizers often exceeds that of bacterial ammonia oxidizers in marine and terrestrial environments but has been understudied in permafrost, where thawing has the potential to release ammonia. Here, three thaumarchaea genomes were assembled and annotated from metagenomic data sets from carbon-poor Canadian High Arctic active-layer cryosols.

Sun, Emily Wei-Hsin↗
DOE OSTI2017

Variations of five eIF4E genes across cassava accessions exhibiting tolerant and susceptible responses to cassava brown streak disease

Cassava (Manihot esculenta) is an important tropical subsistence crop that is severely affected by cassava brown streak disease (CBSD) in East Africa. The disease is caused by Cassava brown streak virus (CBSV) and Ugandan cassava brown streak virus (UCBSV). Both have a (+)-sense single-stranded RNA genome with a 5’ covalently-linked viral protein, which functionally resembles the cap structure of mRNA, binds to eukaryotic translation initiation factor 4E (eIF4E) or its analogues, and then enable the translation of viral genomic RNA in host cells. To characterize cassava eIF4Es and their potential role in CBSD tolerance and susceptibility, we cloned five eIF4E transcripts from cassava (accession TMS60444). Sequence analysis indicated that the cassava eIF4E family of proteins consisted of one eIF4E, two eIF(iso)4E, and two divergent copies of novel cap-binding proteins (nCBPs). Our data demonstrated experimentally the coding of these five genes as annotated in the published cassava genome and provided additional evidence for refined annotations. Illumina resequencing data of the five eIF4E genes were analyzed from 14 cassava lines tolerant or susceptible to CBSD. Abundant single nucleotide polymorphisms (SNP) and biallelic variations were observed in the eIF4E genes; however, most of the SNPs were located in the introns and non-coding regions of the exons. Association studies of non-synonymous SNPs revealed no significant association between any SNP of the five eIF4E genes and the tolerance or susceptibility to CBSD. However, two SNPs in two genes were weakly associated with the CBSD responses but had no direct causal-effect relationship. SNPs in an intergenic region upstream of eIF4E_me showed a surprising strong association with CBSD responses. Digital expression profile analysis showed differential expression of different eIF4E genes but no significant difference in gene expression was found between susceptible and tolerant cassava accessions despite the association of the intergenic SNPs with CBSD responses.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Building a FAIR data ecosystem for incorporating single-cell transcriptomics data into agricultural genome to phenome research

Introduction The agriculture genomics community has numerous data submission standards available, but the standards for describing and storing single-cell (SC, e.g., scRNA- seq) data are comparatively underdeveloped. Methods To bridge this gap, we leveraged recent advancements in human genomics infrastructure, such as the integration of the Human Cell Atlas Data Portal with Terra, a secure, scalable, open-source platform for biomedical researchers to access data, run analysis tools, and collaborate. In parallel, the Single Cell Expression Atlas at EMBL-EBI offers a comprehensive data ingestion portal for high-throughput sequencing datasets, including plants, protists, and animals (including humans). Developing data tools connecting these resources would offer significant advantages to the agricultural genomics community. The FAANG data portal at EMBL-EBI emphasizes delivering rich metadata and highly accurate and reliable annotation of farmed animals but is not computationally linked to either of these resources. Results Herein, we describe a pilot-scale project that determines whether the current FAANG metadata standards for livestock can be used to ingest scRNA-seq datasets into Terra in a manner consistent with HCA Data Portal standards. Importantly, rich scRNA-seq metadata can now be brokered through the FAANG data portal using a semi-automated process, thereby avoiding the need for substantial expert curation. We have further extended the functionality of this tool so that validated and ingested SC files within the HCA Data Portal are transferred to Terra for further analysis. In addition, we verified data ingestion into Terra, hosted on Azure, and demonstrated the use of a workflow to analyze the first ingested porcine scRNA-seq dataset. Additionally, we have also developed prototype tools to visualize the output of scRNA-seq analyses on genome browsers to compare gene expression patterns across tissues and cell populations. This JBrowse tool now features distinct tracks, showcasing PBMC scRNA-seq alongside two bulk RNA-seq experiments. Discussion We intend to further build upon these existing tools to construct a scientist-friendly data resource and analytical ecosystem based on Findable, Accessible, Interoperable, and Reusable (FAIR) SC principles to facilitate SC-level genomic analysis through data ingestion, storage, retrieval, re-use, visualization, and comparative annotation across agricultural species.

Genetics & Heredity↗
DOE OSTI2022

RNAi-Mediated Manipulation of Cuticle Coloration Genes in Lygus hesperus Knight (Hemiptera: Miridae)

Cuticle coloration in insects is a consequence of the accumulation of pigments in a species-specific pattern. Numerous genes are involved in regulating the underlying processes of melanization and sclerotization, and their manipulation can be used to create externally visible markers of successful gene editing. To clarify the roles for many of these genes and examine their suitability as phenotypic markers in Lygus hesperus Knight (western tarnished plant bug), transcriptomic data were screened for sequences exhibiting homology with the Drosophila melanogaster proteins. Complete open reading frames encoding putative homologs for six genes (aaNAT, black, ebony, pale, tan, and yellow) were identified, with two variants for black. Sequence and phylogenetic analyses supported preliminary annotations as cuticle pigmentation genes. In accord with observable difference in color patterning, expression varied for each gene by developmental stage, adult age, body part, and sex. Knockdown by injection of dsRNA for each gene produced varied effects in adults, ranging from the non-detectable (black 1, yellow), to moderate decreases (pale, tan) and increases (black 2, ebony) in darkness, to extreme melanization (aaNAT). Based solely on its expression profile and highly visible phenotype, aaNAT appears to be the best marker for tracking transgenic L. hesperus.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2019

Genome Sequencing of Pleurozium schreberi : The Assembled and Annotated Draft Genome of a Pleurocarpous Feather Moss

The pleurocarpous feather moss Pleurozium schreberi is a ubiquitous moss species which plays a fundamental role in many terrestrial ecosystems, for instance within the boreal forest, the Earth’s largest terrestrial biome, this species plays a significant role in driving ecosystem nitrogen and carbon inputs and fluxes. By hosting dinitrogen (N 2 )-fixing cyanobacteria, the moss-cyanobacteria symbiosis constitutes the main nitrogen input into the ecosystem and by the high productivity and the low decomposability of the moss litter, P. schreberi contributes significantly to build-up soil organic matter, and therefore long-term C sequestration. Knowledge on P. schreberi genome will facilitate the development of ‘omics’ and system’s biology approaches to gain a more complete understanding of the physiology and ecological adaptation of the moss and the mechanisms underpinning the establishment of the symbiosis. Here we present the de novo assembly and annotation of P. schreberi genome that will help investigating these questions. The sequencing was performed using the HiSeq X platform with Illumina paired-end and mate-pair libraries prepared with CTAB extracted DNA. In total, the assembled genome was approximately 318 Mb, while repetitive elements account for 28.42% of the genome and 15,992 protein-coding genes were predicted from the genome, of which 84.23% have been functionally annotated. We anticipate that the genomic data generated will constitute a significant resource to study ecological and evolutionary genomics of P. schreberi, and will be valuable for evo-devo investigations as well as our understanding of the evolution of land plants by providing the genome of a pleurocarpous moss.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

DOE JGI Metagenome Workflow

The DOE Joint Genome Institute (JGI) Metagenome Workflow performs metagenome data processing, including assembly; structural, functional, and taxonomic annotation; and binning of metagenomic data sets that are subsequently included into the Integrated Microbial Genomes and Microbiomes (IMG/M) (I.-M. A. Chen, K. Chu, K. Palaniappan, A. Ratner, et al., Nucleic Acids Res, 49:D751–D763, 2021, https://doi.org/10.1093/nar/gkaa939) comparative analysis system and provided for download via the JGI data portal (https://genome.jgi.doe.gov/portal/). This workflow scales to run on thousands of metagenome samples per year, which can vary by the complexity of microbial communities and sequencing depth. Here, we describe the different tools, databases, and parameters used at different steps of the workflow to help with the interpretation of metagenome data available in IMG and to enable researchers to apply this workflow to their own data. We use 20 publicly available sediment metagenomes to illustrate the computing requirements for the different steps and highlight the typical results of data processing. The workflow modules for read filtering and metagenome assembly are available as a workflow description language (WDL) file (https://code.jgi.doe.gov/BFoster/jgi_meta_wdl). The workflow modules for annotation and binning are provided as a service to the user community at https://img.jgi.doe.gov/submit and require filling out the project and associated metadata descriptions in the Genomes OnLine Database (GOLD) (S. Mukherjee, D. Stamatis, J. Bertsch, G. Ovchinnikova, et al., Nucleic Acids Res, 49:D723–D733, 2021, https://doi.org/10.1093/nar/gkaa983).

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Coupling Metabolic Source Isotopic Pair Labeling and Genome Wide Association for Metabolite and Gene Annotation in Plants (Final Technical Report)

In this project, we applied our labeling pipeline to Arabidopsis and sorghum by feeding tissues with isotopically labeled versions of commercially available amino acids to identify all metabolite features that incorporate the label. In sorghum, we fed five accessions, sampled across the diversity of sorghum, to identify the precursor-of-origin for metabolites that vary between accessions as well as those that may be missing from a single reference genotype. This provided us with precursor-of-origin annotation for thousands of unknown metabolites. We then used GWA to map genes responsible for the synthesis of precursor-of-origin classified metabolites. For sorghum leaf and root ducible metabolites, we performed untargeted metabolomics on leaf and root tissues from 300 diverse genotyped sorghum inbred lines. The amino acid precursor-of-origin metabolite library were then used to identify the corresponding metabolites in the GWA data sets and to identify novel gene-metabolite associations. Finally, we utilized existing and newly generated sequenced EMS mutants of sorghum to validate the predicted gene-metabolite relationships that our labelling analysis identified. In parallel, we conducted similar feeding experiments in Arabidopsis to categorize metabolites based on precursor-of-origin, identify those that vary across our existing Arabidopsis metabolite GWA dataset, and identify genes required for the synthesis of each metabolite. To provide an independent test of gene annotation and pathway involvement, we tested the GWA gene-metabolite associations in Arabidopsis by analyzing the metabolic phenotypes of gene knockouts. Genes of particular interest from both sorghum and Arabidopsis were studied in detail by directly measuring the activity of the corresponding enzymes following heterologous expression. In summary, this work classified as-yet-unknown amino acid-derived metabolites and identified genes involved in their production generated through “omics” technologies. This information was used to validate gene function and identify new metabolism in Arabidopsis and sorghum.

09 BIOMASS FUELS↗
DOE OSTI2019

Exploiting the Dynamic Relationship between Peptide Separation Quality and Peptide Coisolation in a Multiple-Peptide Matches-per-Spectrum Approach Offers a Strategy To Optimize Bottom-Up Proteomics Throughput and Depth

We present that peptide cofragmentation leads to chimeric MS/MS spectra that negatively impact traditional single-peptide match-per-spectrum (sPSM) search strategies in proteomics. The collection of chimeric spectra is influenced by peptide coelution and the width of precursor isolation windows. Although peptide cofragmentation can be reduced by advanced chromatography, such as UHPLC and 2D-HPLC separation schemes, and narrower isolation windows, chimeric spectra can still be as high as 30–50% of the total MS/MS spectra collected. Alternatively, cofragmented peptides in chimeric spectra and the use of wider isolation windows benefit multiple-peptide matches-per-spectrum (mPSM) algorithms, such as CharmeRT, which facilitate the identification of several cofragmented peptides. Considering recent advancements in LC and mPSM methodologies, we present a comprehensive examination of the levels of chimeric spectra collected in the analysis of a HeLa digest measured using different LC modes of separation and isolation windows and compare the depth of identifications obtained when these data are annotated using a sPSM or a mPSM approach. Our results demonstrate that MS/MS data derived from 1D-HPLC strategies under different gradient schemes and searched with CharmeRT yielded higher average numbers of PSMs (11%–49%), peptide analytes (10%–16%), and peptide sequences (3%–10%) compared to data derived from 1D-UHPLC runs but searched with a sPSM strategy. Interestingly, data from a 2D-HPLC separation strategy benefits more from the application of CharmeRT results when compared to a 50 cm 1D-UHPLC column employing a 500 min gradient. In conclusion, these results provide new insights into how to better configure LC-MS/MS measurements for improved throughput and peptide identification in complex proteomes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

RolyPoly (rp) v0.1.0

The Rolypoly pipeline is designed to process raw RNA-seq data and identify potential RNA viral sequences. It is split into several self contained steps: 1. input data filtering and QC, 2. Genome assembly and refinement, 3. Assembly filtering, 4. Mapping to known RNA viral genomes, 5. Searching for RNA viral marker genes. 6. Genome functional and structural annotation. 6. Report preparation and potential downstream analysis The last module, may include taxonomic assignment, host range estimation, and phenotypic prediction. There are many similar software, but they focus on human related viruses, and lack the downstream applications or differ in their sensitivity. The initial user base are non-computational microbial ecologists who wish to better understand the potential RNA viruses in their own generated samples.

Neri, Uri↗
DOE OSTI2017

Draft genome sequence of Actinotignum schaalii DSM 15541 T : Genetic insights into the lifestyle, cell fitness and virulence

The permanent draft genome sequence of Actinotignum schaalii DSM 15541 T is presented. The annotated genome includes 2,130,987 bp, with 1777 protein-coding and 58 rRNA-coding genes. Genome sequence analysis revealed absence of genes encoding for: components of the PTS systems, enzymes of the TCA cycle, glyoxylate shunt and gluconeogensis. Genomic data revealed that A. schaalii is able to oxidize carbohydrates via glycolysis, the nonoxidative pentose phosphate and the Entner-Doudoroff pathways. Besides, the genome harbors genes encoding for enzymes involved in the conversion of pyruvate to lactate, acetate and ethanol, which are found to be the end products of carbohydrate fermentation. The genome contained the gene encoding Type I fatty acid synthase required for de novo FAS biosynthesis. The plsY and plsX genes encoding the acyltransferases necessary for phosphatidic acid biosynthesis were absent from the genome. The genome harbors genes encoding enzymes responsible for isoprene biosynthesis via the mevalonate (MVA) pathway. Genes encoding enzymes that confer resistance to reactive oxygen species (ROS) were identified. In addition, A. schaalii harbors genes that protect the genome against viral infections. These include restriction-modification (RM) systems, type II toxin-antitoxin (TA), CRISPR-Cas and abortive infection system. A. schaalii genome also encodes several virulence factors that contribute to adhesion and internalization of this pathogen such as the tad genes encoding proteins required for pili assembly, the nanI gene encoding exo-alpha-sialidase, genes encoding heat shock proteins and genes encoding type VII secretion system. These features are consistent with anaerobic and pathogenic lifestyles. Finally, resistance to ciprofloxacin occurs by mutation in chromosomal genes that encode the subunits of DNA-gyrase (GyrA) and topisomerase IV (ParC) enzymes, while resistant to metronidazole was due to the frxA gene, which encodes NADPH-flavin oxidoreductase.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Make the Most Out of Genome Announcements with KBase

Genomics is a dynamic field driven by new technology, massive growth in data, and changes in how scientists share knowledge. This brings new challenges for researchers looking to maximize the impact of their science and ensure the longevity of their data. These changes are especially relevant for the practice of publishing genome announcements. Genome announcements are meant to share and promote newly sequenced organisms with the larger scientific community. A few decades ago, genome announcements were highly anticipated hallmarks of novel science. But, what was once a publishing coup is now an every day event. It is harder and harder to keep abreast of all the genomes that have been sequenced and promote your own new genomes to get the attention and recognition of your research community. Fortunately, KBase can help construct genomes from your sequencing data, generate reports for your announcement, and promote your data to your research community.

59 BASIC BIOLOGICAL SCIENCES↗