Biology subjects

Brown, C. T.

Publications and source records attributed to Brown, C. T..

35 records · Page 2Linked to original sources

bioRxiv2020

Streamlining Data-Intensive Biology With Workflow Systems

As the scale of biological data generation has increased, the bottleneck of research has shifted from data generation to analysis. Researchers commonly need to build computational workflows that include multiple analytic tools and require incremental development as experimental insights demand tool and parameter modifications. These workflows can produce hundreds to thousands of intermediate files and results that must be integrated for biological insight. Data-centric workflow systems that internally manage computational resources, software, and conditional execution of analysis steps are reshaping the landscape of biological data analysis, and empowering researchers to conduct reproducible analyses at scale. Adoption of these tools can facilitate and expedite robust data analysis, but knowledge of these techniques is still lacking. Here, we provide a series of practices and strategies for leveraging workflow systems with structured project, data, and resource management to streamline large-scale biological analysis. We present these strategies in the context of high-throughput sequencing data analysis, but the principles are broadly applicable to biologists working beyond this field. Author SummaryWe present a guide for workflow-enabled biological sequence data analysis, developed through our own teaching, training and analysis projects. We recognize that this is based on our own use cases and experiences, but we hope that our guide will contribute to a larger discussion within the open source and open science communities and lead to more comprehensive resources. Our main goal is to accelerate the research of scientists conducting sequence analyses by introducing them to organized workflow practices that not only benefit their own research but also facilitate open and reproducible science.

bioinformatics↗

bioRxiv2020

Genomic characterization of a diazotrophic microbiota associated with maize aerial root mucilage

A geographically isolated maize landrace cultivated on nitrogen-depleted fields without synthetic fertilizer in the Sierra Mixe region of Oaxaca, Mexico utilizes nitrogen derived from the atmosphere and develops an extensive network of mucilage-secreting aerial roots that harbors a diazotrophic microbiota. Targeting these diazotrophs, we selected nearly 600 microbes from a collection isolated from these plants and confirmed their ability to incorporate heavy nitrogen (15N2) metabolites in vitro. Sequencing their genomes and conducting comparative bioinformatic analyses showed that these genomes had substantial phylogenetic diversity. We examined each diazotroph genome for the presence of nif genes essential to nitrogen fixation (nifHDKENB) and carbohydrate utilization genes relevant to the mucilage polysaccharide digestion. These analyses identified diazotrophs that possessed canonical nif gene operons, as well as many other operon configurations with concomitant fixation and release of >700 different 15N labeled metabolites. We further demonstrated that many diazotrophs possessed alternative nif gene operons and confirmed their genomic potential to derive chemical energy from mucilage polysaccharide to fuel nitrogen fixation. These results confirm that some diazotrophic bacteria associated with Sierra Mixe maize were capable of incorporating atmospheric nitrogen into their small molecule extracellular metabolites through multiple nif gene configurations while others were able to fix nitrogen without the canonical (nifHDKENB) genes. Data SummaryGenetic resources, including biological materials and nucleic acid sequences, were accessed under an Access and Benefit Sharing (ABS) Agreement between the Sierra Mixe community and the Mars Corporation, and with authorization from the Mexican government. An internationally recognized certificate of compliance has been issued by the Mexican government under the Nagoya Protocol for such activities (ABSCH-IRCC-MX-207343-3). Any party seeking access to the nucleic acid sequences underlying the analysis reported here is subject to the full terms and obligations of the ABS agreement and the authorization from the government of Mexico. Individuals wishing to access nucleic acid sequence data for scientific research activities should contact Mars Incorporated Chief Science Officer at CSO@effem.com.

genomics↗

bioRxiv2020

Whole genome assembly of Culex tarsalis

The mosquito, Culex tarsalis, is a key vector in the western United States due to its role in transmission of zoonotic arboviruses that affect human health. Extensive research has been conducted on Cx. tarsalis ecology, feeding behavior, vector competence, autogeny, diapause, genetics, and insecticide resistance. Population genetic analyses in the western U.S. have identified at least three genetic clusters that are geographically distinct. Salivary gland-specific gene expression has also revealed genes involved in blood feeding. However, genetic studies of this mosquito have been hindered by the lack of a reference genome. To facilitate genomic studies in Cx. tarsalis, we have assembled and annotated a reference genome (CtarK1) based on PacBio HiFi reads from a single male. Using the Cx. tarsalis transcriptome and protein sequences from Culex quinquefasciatus, approximately 17,456 protein-coding genes, including the para insecticide resistance gene, were annotated in the CtarK1 genome. Genome completeness was assessed using the Benchmarking Universal Single-Copy Orthologs (BUSCO) tool, which identified 84.8% of the 2799 Dipteran BUSCO genes. The CtarK1 assembly is 790Mb with an N50 of 58kb. Using full mitochondrial genome alignments with other sequenced mosquito genomes we present a Bayesian phylogeny, which estimates that the divergence of Cx. tarsalis from Culex quinquefasciatus, the most closely related mosquito species with a genome, occurred 15.8-22.2 million years ago.

genomics↗

bioRxiv2019

Large-scale sequence comparisons with sourmash

The sourmash software package uses MinHash-based sketching to create \"signatures\", compressed representations of DNA, RNA, and protein sequences, that can be stored, searched, explored, and taxonomically annotated. sourmash signatures can be used to estimate sequence similarity between very large data sets quickly and in low memory, and can be used to search large databases of genomes for matches to query genomes and metagenomes. sourmash is implemented in C++, Rust, and Python, and is freely available under the BSD license at http://github.com/dib-lab/sourmash.

bioinformatics↗

bioRxiv2019

Draft genome assemblies using sequencing reads from Oxford Nanopore Technology and Illumina platforms for four species of North American killifish from the Fundulus genus

Draft de novo reference genome assemblies were obtained from four North American killifish species (Fundulus xenicus, Fundulus catenatus, Fundulus nottii, and Fundulus olivaceus) using sequence reads from Illumina and Oxford Nanopore Technologies PromethION platforms. For each species, the PromethION platform was used to generate 30-45x sequence coverage, and the Illumina platform was used to generate 50-160x sequence coverage. Contig N50 values ranged from 0.4 Mb to 2.7 Mb, and BUSCO scores were consistently above 90% complete using the Eukaryota database. Draft assemblies and raw sequencing data are available for public use. We encourage use and re-use of these data for assembly benchmarking and external analyses.

genomics↗

bioRxiv2019

FAIRshake: toolkit to evaluate the findability, accessibility, interoperability, and reusability of research digital resources

As more datasets, tools, workflows, APIs, and other digital resources are produced by the research community, it is becoming increasingly difficult to harmonize and organize these efforts for maximal synergistic integrated utilization. The Findable, Accessible, Interoperable, and Reusable (FAIR) guiding principles have prompted many stakeholders to consider strategies for tackling this challenge by making these digital resources follow common standards and best practices so that they can become more integrated and organized. Faced with the question of how to make digital resources more FAIR, it has become imperative to measure what it means to be FAIR. The diversity of resources, communities, and stakeholders have different goals and use cases and this makes assessment of FAIRness particularly challenging. To begin resolving this challenge, the FAIRshake toolkit was developed to enable the establishment of community-driven FAIR metrics and rubrics paired with manual, semi- and fully-automated FAIR assessment capabilities. The FAIRshake toolkit contains a database that lists registered digital resources, with their associated metrics, rubrics, and assessments. The FAIRshake toolkit also has a browser extension and a bookmarklet that enables viewing and submitting assessments from any website. The FAIR assessment results are visualized as an insignia that can be viewed on the FAIRshake website, or embedded within hosting websites. Using FAIRshake, a variety of bioinformatics tools, datasets listed on dbGaP, APIs registered in SmartAPI, workflows in Dockstore, and other biomedical digital resources were manually and automatically assessed for FAIRness. In each case, the assessments revealed room for improvement, which prompted enhancements that significantly upgraded FAIRness scores of several digital resources.

bioinformatics↗

bioRxiv2019

Kevlar: a mapping-free framework for accurate discovery of de novo variants

MotivationDiscovery of genetic variants by whole genome sequencing has proven a powerful approach to study the etiology of complex genetic disorders. Elucidation of all variants is a necessary step in identifying causative variants and disease genes. In particular, there is an increased interest in detection of de novo variation and investigation of its role in various disorders. State-of-the-art methods for variant discovery rely on mapping reads from each individual to a reference genome and predicting variants from difference observed between the mapped reads and the reference genome. This process typically results in millions of variant predictions, most of which are inherited and irrelevant to the phenotype of interest. To distinguish between inherited variation and novel variation resulting from de novo germline mutation, whole-genome sequencing of close relatives (especially parents and siblings) is commonly used. However, standard mapping-based approaches tend to have a high false-discovery rate for de novo variant prediction, which in many cases arises from problems with read mapping. This is a particular challenge in predicting de novo indels and structural variants. ResultsWe have developed a mapping-free method, Kevlar, for de novo variant discovery based on direct comparison of sequence content between related individuals. Kevlar identifies high-abundance k-mers unique to the individual of interest and retrieves the reads containing these k-mers. These reads are easily partitioned into disjoint sets by shared k-mer content for subsequent locus-by-locus processing and variant calling. Kevlar also utilizes a novel probabilistic approach to score and rank the variant predictions to identify the most likely de novo variants. We evaluated Kevlar on simulated and real pedigrees, and demonstrate its ability to detect both de novo SNVs and indels with high sensitivity and specificity. Availability: https://github.com/dib-lab/kevlar

bioinformatics↗

bioRxiv2018

Microbial contamination in the genome of the domesticated olive

Draft genomes of both the wild and domesticated olive were recently published. While working with these genomes, we identified contamination in the domesticated olive genome representing .06% of basepairs and 1.3% of scaffolds. We used targeted and untargeted approaches to identify the contaminating sequences, the majority of which were Aureobasidium pullulans. We applied the same method to the wild olive genome and did not find evidence of contamination. Although contamination in the domesticated olive genome was not prolific, it could lead to biased results either from functional content encoded in the contaminant sequences, or from using it to separate microbial reads from olive reads in microbiome studies.

genomics↗

bioRxiv2018

Shifts in microbial transcription patterns prior to onset of Necrotizing enterocolitis may indicate low oxygen levels in the gut

Premature infants are at risk for developing necrotizing enterocolitis (NEC), an inflammatory disease that can progress to necrosis of gut tissue. Previous attempts have failed to identify any consistent predictor of NEC. We hypothesized that prior to the appearance of NEC symptoms, the gut microbiome shifts in its transcriptional profile. To test this hypothesis we integrated genome-resolved metagenomic and metatranscriptomic data from multiple time-points in the first month of life of four preterm infants, two of whom later developed NEC. Gut microbiomes of NEC infants showed increased transcription of high oxygen affinity cytochrome oxidases and lower transcription of genes to detoxify nitric oxide, an antimicrobial compound released by host cells. These results, and high transcription of H2 production genes, suggest low O2 conditions prior to NEC onset, and are consistent with hypoxic conditions in diseased gut tissue. The findings motivate further testing of transcript data as a predictor of NEC.\n\nHighlightsO_LITranscription of high oxygen affinity microbial cytochrome oxidase may predict necrotizing enterocolitis (NEC) development.\nC_LIO_LILower transcription of microbial genes to detoxify nitric oxide (NO) may also predict NEC development.\nC_LIO_LIHigher transcription of H2 production genes by Escherichia sp. was found in the gut of premature infants that develop NEC.\nC_LI

microbiology↗

bioRxiv2018

Exploring neighborhoods in large metagenome assembly graphs reveals hidden sequence diversity

Genomes computationally inferred from large metagenomic data sets are often incomplete and may be missing functionally important content and strain variation. We introduce an information retrieval system for large metagenomic data sets that exploits the sparsity of DNA assembly graphs to efficiently extract subgraphs surrounding an inferred genome. We apply this system to recover missing content from genome bins and show that substantial genomic sequence variation is present in a real metagenome. Our software implementation is available at https://github.com/spacegraphcats/ spacegraphcats under the 3-Clause BSD License.

bioinformatics↗

bioRxiv2018

Comparing faster evolving rplB and rpsC versus SSU rRNA for improved microbial community resolution

Many conserved protein-coding core genes are single copy and evolve faster, and thus are more resolving phylogenetic markers than the standard SSU rRNA gene but their use has been precluded by the lack of universal primers. Recent advances in gene targeted assembly methods for large shotgun metagenomes make their use feasible. To evaluate this approach, we compared the variation of two single copy ribosomal protein genes, rplB and rpsC, with the SSU rRNA gene for all completed bacterial genomes in NCBI RefSeq. As expected, among pairwise comparisons of all species that belong to the same genus, 94.9% and 91.0% of the pairs of rplB and rpsC, respectively, showed more variation than did their SSU rRNA gene sequences. We used a gene-targeted assembler, Xander, to assemble rplB and rpsC from shotgun metagenomic data from rhizosphere samples of three crops: corn (annual), and Miscanthus and switchgrass (both perennials). Both protein-coding genes separated all three communities whereas the SSU rRNA gene could only separate the annual from the two perennial communities in ordination analyses. Furthermore, assembled rplB and rpsC yielded significantly higher numbers of OTUs (alpha diversity) than the SSU rRNA gene. These results confirm these faster evolving marker genes offer increased resolution of for comparative microbiome studies.

microbiology↗

bioRxiv2018

Insights into the evolution of oxygenic photosynthesis from a phylogenetically novel, low-light cyanobacterium

Atmospheric oxygen level rose dramatically around 2.4 billion years ago due to oxygenic photosynthesis by the Cyanobacteria. The oxidation of surface environments permanently changed the future of life on Earth, yet the evolutionary processes leading to oxygen production are poorly constrained. Partial records of these evolutionary steps are preserved in the genomes of organisms phylogenetically placed between non-photosynthetic Melainabacteria, crown-group Cyanobacteria, and Gloeobacter, representing the earliest-branching Cyanobacteria capable of oxygenic photosynthesis. Here, we describe nearly complete, metagenome assembled genomes of an uncultured organism phylogenetically placed between the Melainabacteria and crown-group Cyanobacteria, for which we propose the name Candidatus Aurora vandensis {au.rora Latin noun dawn and vand.ensis, originating from Vanda}.\n\nThe metagenome assembled genome of A. vandensis contains homologs of most genes necessary for oxygenic photosynthesis including key reaction center proteins. Many extrinsic proteins associated with the photosystems in other species are, however, missing or poorly conserved. The assembled genome also lacks homologs of genes associated with the pigments phycocyanoerethrin, phycoeretherin and several structural parts of the phycobilisome. Based on the content of the genome, we propose an evolutionary model for increasing efficiency of oxygenic photosynthesis through the evolution of extrinsic proteins to stabilize photosystem II and I reaction centers and improve photon capture. This model suggests that the evolution of oxygenic photosynthesis may have significantly preceded oxidation of Earths atmosphere due to low net oxygen production by early Cyanobacteria.

microbiology↗

bioRxiv2018

Re-assembly, quality evaluation, and annotation of 678 microbial eukaryotic reference transcriptomes

BackgroundDe novo transcriptome assemblies are required prior to analyzing RNAseq data from a species without an existing reference genome or transcriptome. Despite the prevalence of transcriptomic studies, the effects of using different workflows, or \"pipelines\", on the resulting assemblies are poorly understood. Here, a pipeline was programmatically automated and used to assemble and annotate raw transcriptomic short read data collected by the Marine Microbial Eukaryotic Transcriptome Sequencing Project (MMETSP). The resulting transcriptome assemblies were evaluated and compared against assemblies that were previously generated with a different pipeline developed by the National Center for Genome Research (NCGR).\n\nResultsNew transcriptome assemblies contained the majority of previous contigs as well as new content. On average, 7.8% of the annotated contigs in the new assemblies were novel gene names not found in the previous assemblies. Taxonomic trends were observed in the assembly metrics, with assemblies from the Dinoflagellata and Ciliophora phyla showing a higher percentage of open reading frames and number of contigs than transcriptomes from other phyla.\n\nConclusionsGiven current bioinformatics approaches, there is no single best reference transcriptome for a particular set of raw data. As the optimum transcriptome is a moving target, improving (or not) with new tools and approaches, automated and programmable pipelines are invaluable for managing the computationally-intensive tasks required for re-processing large sets of samples with revised pipelines and ensuring a common evaluation workflow is applied to all samples. Thus, re-assembling existing data with new tools using automated and programmable pipelines may yield more accurate identification of taxon-specific trends across samples in addition to novel and useful products for the community.\n\nKey PointsO_LIRe-assembly with new tools can yield new results\nC_LIO_LIAutomated and programmable pipelines can be used to process arbitrarily many samples.\nC_LIO_LIAnalyzing many samples using a common pipeline identifies taxon-specific trends.\nC_LI

bioinformatics↗

bioRxiv2017

Hospitalized premature infants are colonized by related bacterial strains with distinct proteomic profiles

During the first weeks of life, microbial colonization of the gut impacts human immune system maturation and other developmental processes. In premature infants, aberrant colonization has been implicated in the onset of necrotizing enterocolitis (NEC), a life-threatening intestinal disease. To study the premature infant gut colonization process, genome-resolved metagenomics was conducted on 343 fecal samples collected during the first three months of life from 35 premature infants housed in a neonatal intensive care unit, 14 of which developed NEC, and metaproteomic measurements were made on 87 samples. Microbial community composition and proteomic profiles remained relatively stable on the time scale of a week, but the proteome was more variable. Although genetically similar organisms colonized many infants, most infants were colonized by distinct strains with metabolic profiles that could be distinguished using metaproteomics. Microbiome composition correlated with infant, antibiotics administration, and NEC diagnosis. Communities were found to cluster into seven primary types, and community type switched within infants, sometimes multiple times. Interestingly, some communities sampled from the same infant at subsequent time points clustered with those of other infants. In some cases, switches preceded onset of NEC; however, no species or community type could account for NEC across the majority of infants. In addition to a correlation of protein abundances with organism replication rates, we found that organism proteomes correlated with overall community composition. Thus, this genome-resolved proteomics study demonstrates that the contributions of individual organisms to microbiome development depend on microbial community context.\n\nImportance\n\nHumans are colonized by microbes at birth, a process that is important to health and development. However, much remains to be known about the fine-scale microbial dynamics that occur during the colonization period. We conducted a genome-resolved study of microbial community composition, replication rates, and proteomes during the first three months of life of both healthy and sick premature infants. Infants were found to be colonized by similar microbes, but each underwent a distinct colonization trajectory.\n\nInterestingly, related microbes colonizing different infants were found to have distinct proteomes, indicating that microbiome function is not only driven by which organisms are present, but also largely depends on microbial responses to the unique set of physiological conditions in the infant gut.

microbiology↗

bioRxiv2017

Evaluating Metagenome Assembly on a Simple Defined Community with Many Strain Variants

We evaluate the performance of three metagenome assemblers, IDBA, MetaSPAdes, and MEGAHIT, on short-read sequencing of a defined \"mock\" community containing 64 genomes (Shakya et al. (2013)). We update the reference metagenome for this mock community and detect several additional genomes in the read data set. We show that strain confusion results in significant loss in assembly of reference genomes that are otherwise completely present in the read data set. In agreement with previous studies, we find that MEGAHIT performs best computationally; we also show that MEGAHIT tends to recover larger portions of the strain variants than the other assemblers.

bioinformatics↗

bioRxiv2017

FGF4 Retrogene On CFA12 Is Responsible For Chondrodystrophy And Intervertebral Disc Disease In Dogs

Chondrodystrophy in dogs is defined by dysplastic, shortened long bones and premature degeneration and calcification of intervertebral discs. Independent genome-wide association analyses for skeletal dysplasia (short limbs) within a single breed (pBonferroni=0.0072) and intervertebral disc disease (IVDD) across breeds (pBonferroni=4.02x10-10) both identified a significant association to the same region on CFA12. Whole genome sequencing identified a highly expressed FGF4 retrogene within this shared region. The FGF4 retrogene segregated with limb length and had an odds ratio of 51.23 (95% CI = 46.69, 56.20) for IVDD. Long bone length in dogs is a unique example of multiple disease-causing retrocopies of the same parental gene in a mammalian species. FGF signaling abnormalities have been associated with skeletal dysplasia in humans, and our findings present opportunities for both selective elimination of a medically and financially devastating disease in dogs and further understanding of the ever-growing complexity of retrogene biology.

genetics↗

bioRxiv2017

dRep: A tool for fast and accurate genome de-replication that enables tracking of microbial genotypes and improved genome recovery from metagenomes

The number of microbial genomes sequenced each year is expanding rapidly, in part due to genome-resolved metagenomic studies that routinely recover hundreds of draft-quality genomes. Rapid algorithms have been developed to comprehensively compare large genome sets, but they are not accurate with draft-quality genomes. Here we present dRep, a program that sequentially applies a fast, inaccurate estimation of genome distance and a slow but accurate measure of average nucleotide identity to reduce the computational time for pair-wise genome set comparisons by orders of magnitude. We demonstrate its use in a study where we separately assembled each metagenome from time series datasets. Groups of essentially identical genomes were identified with dRep, and the best genome from each set was selected. This resulted in recovery of significantly more and higher-quality genomes compared to the set recovered using the typical co-assembly method. Documentation is available at http://drep.readthedocs.io/en/master/ and source code is available at https://github.com/MrOlm/drep.

bioinformatics↗