Raw pacific biosciences and illumina sequencing reads and assembled genome data for the cattle ticks Rhipicephalus microplus and Rhipicephalus annulatus

Ticks from the genus Rhipicephalus have enormous global economic impact as ectoparasites of cattle. Rhipicephalus microplus and Rhipicephalus annulatus are known to harbor infectious pathogens such as Babesia bovis, Babesia bigemina, and Anaplasma marginale. Having reference quality genomes of these ticks would advance research to identify druggable targets for chemical entities with acaricidal activity and refine anti-tick vaccine approaches. We sequenced and assembled the genomes of R. microplus and R. annulatus, using Pacific Biosciences and HiSeq 4000 technologies on very high molecular weight genomic DNA. We used 22 and 29 SMRT cells on the Pacific Biosciences Sequel for R. microplus and R. annulatus, respectively, and 3 lanes of the Illumina HiSeq 4000 platform for each tick. The PacBio sequence yields for R. microplus and R. annulatus were 21.0 and 27.9 million subreads, respectively, which were assembled with Canu v. 1.7. The final Canu assemblies consisted of 92,167 and 57,796 contigs with an average contig length of 39,249 and 69,055 bp for R. microplus and R. annulatus, respectively. Annotated genome quality was assessed by BUSCO analysis to provide quantitative measures for each assembled genome. Over 82% and 92% of the 1066 member BUSCO gene set was found in the assembled genomes of R. microplus and R. annulatus, respectively. For R. microplus, only 189 of the 1066 BUSCO genes were missing and only 140 were present in a fragmented condition. For R. annulatus, only 75 of the BUSCO genes were missing and only 109 were present in a fragmented condition. The raw sequencing reads and the assembled contigs/scaffolds are archived at the National Center for Biotechnology Information.

The human body at cellular resolution: the NIH Human Biomolecular Atlas Program

Transformative technologies are enabling the construction of three-dimensional maps of tissues with unprecedented spatial and molecular resolution. Over the next seven years, the NIH Common Fund Human Biomolecular Atlas Program (HuBMAP) intends to develop a widely accessible framework for comprehensively mapping the human body at single-cell resolution by supporting technology development, data acquisition, and detailed spatial mapping. HuBMAP will integrate its efforts with other funding agencies, programs, consortia, and the biomedical research community at large towards the shared vision of a comprehensive, accessible three-dimensional molecular and cellular atlas of the human body, in health and under various disease conditions.

Critical Assessment of Metagenome Interpretation-a benchmark of metagenomics software

Methods for assembly, taxonomic profiling and binning are key to interpreting metagenome data, but a lack of consensus about benchmarking complicates performance assessment. The Critical Assessment of Metagenome Interpretation (CAMI) challenge has engaged the global developer community to benchmark their programs on highly complex and realistic data sets, generated from ∼700 newly sequenced microorganisms and ∼600 novel viruses and plasmids and representing common experimental setups. Assembly and genome binning programs performed well for species represented by individual genomes but were substantially affected by the presence of related strains. Taxonomic profiling and binning programs were proficient at high taxonomic ranks, with a notable performance decrease below family level. Parameter settings markedly affected performance, underscoring their importance for program reproducibility. The CAMI results highlight current challenges but also provide a roadmap for software selection to answer specific research questions.

Critical Assessment of Metagenome Interpretation-a benchmark of metagenomics software

Methods for assembly, taxonomic profiling and binning are key to interpreting metagenome data, but a lack of consensus about benchmarking complicates performance assessment. The Critical Assessment of Metagenome Interpretation (CAMI) challenge has engaged the global developer community to benchmark their programs on highly complex and realistic data sets, generated from ∼700 newly sequenced microorganisms and ∼600 novel viruses and plasmids and representing common experimental setups. Assembly and genome binning programs performed well for species represented by individual genomes but were substantially affected by the presence of related strains. Taxonomic profiling and binning programs were proficient at high taxonomic ranks, with a notable performance decrease below family level. Parameter settings markedly affected performance, underscoring their importance for program reproducibility. The CAMI results highlight current challenges but also provide a roadmap for software selection to answer specific research questions.

TCGA Expedition: A Data Acquisition and Management System for TCGA Data

Background

The Cancer Genome Atlas Project (TCGA) is a National Cancer Institute effort to profile at least 500 cases of 20 different tumor types using genomic platforms and to make these data, both raw and processed, available to all researchers. TCGA data are currently over 1.2 Petabyte in size and include whole genome sequence (WGS), whole exome sequence, methylation, RNA expression, proteomic, and clinical datasets. Publicly accessible TCGA data are released through public portals, but many challenges exist in navigating and using data obtained from these sites. We developed TCGA Expedition to support the research community focused on computational methods for cancer research. Data obtained, versioned, and archived using TCGA Expedition supports command line access at high-performance computing facilities as well as some functionality with third party tools. For a subset of TCGA data collected at University of Pittsburgh, we also re-associate TCGA data with de-identified data from the electronic health records. Here we describe the software as well as the architecture of our repository, methods for loading of TCGA data to multiple platforms, and security and regulatory controls that conform to federal best practices.

Results

TCGA Expedition software consists of a set of scripts written in Bash, Python and Java that download, extract, harmonize, version and store all TCGA data and metadata. The software generates a versioned, participant- and sample-centered, local TCGA data directory with metadata structures that directly reference the local data files as well as the original data files. The software supports flexible searches of the data via a web portal, user-centric data tracking tools, and data provenance tools. Using this software, we created a collaborative repository, the Pittsburgh Genome Resource Repository (PGRR) that enabled investigators at our institution to work with all TCGA data formats, and to interrogate these data with analysis pipelines, and associated tools. WGS data are especially challenging for individual investigators to use, due to issues with downloading, storage, and processing; having locally accessible WGS BAM files has proven invaluable.

Conclusion

Our open-source, freely available TCGA Expedition software can be used to create a local collaborative infrastructure for acquiring, managing, and analyzing TCGA data and other large public datasets.

Novel transcriptome assembly and improved annotation of the whiteleg shrimp (Litopenaeus vannamei), a dominant crustacean in global seafood mariculture

We present a new transcriptome assembly of the Pacific whiteleg shrimp (Litopenaeus vannamei), the species most farmed for human consumption. Its functional annotation, a substantial improvement over previous ones, is provided freely. RNA-Seq with Illumina HiSeq technology was used to analyze samples extracted from shrimp abdominal muscle, hepatopancreas, gills and pleopods. We used the Trinity and Trinotate software suites for transcriptome assembly and annotation, respectively. The quality of this assembly and the affiliated targeted homology searches greatly enrich the curated transcripts currently available in public databases for this species. Comparison with the model arthropod Daphnia allows some insights into defining characteristics of decapod crustaceans. This large-scale gene discovery gives the broadest depth yet to the annotated transcriptome of this important species and should be of value to ongoing genomics and immunogenetic resistance studies in this shrimp of paramount global economic importance.

Enabling large-scale next-generation sequence assembly with Blacklight

A variety of extremely challenging biological sequence analyses were conducted on the XSEDE large shared memory resource Blacklight, using current bioinformatics tools and encompassing a wide range of scientific applications. These include genomic sequence assembly, very large metagenomic sequence assembly, transcriptome assembly, and sequencing error correction. The data sets used in these analyses included uncategorized fungal species, reference microbial data, very large soil and human gut microbiome sequence data, and primate transcriptomes, composed of both short-read and long-read sequence data. A new parallel command execution program was developed on the Blacklight resource to handle some of these analyses. These results, initially reported previously at XSEDE13 and expanded here, represent significant advances for their respective scientific communities. The breadth and depth of the results achieved demonstrate the ease of use, versatility, and unique capabilities of the Blacklight XSEDE resource for scientific analysis of genomic and transcriptomic sequence data, and the power of these resources, together with XSEDE support, in meeting the most challenging scientific problems.

Leveraging the national cyberinfrastructure for biomedical research

In the USA, the national cyberinfrastructure refers to a system of research supercomputer and other IT facilities and the high speed networks that connect them. These resources have been heavily leveraged by scientists in disciplines such as high energy physics, astronomy, and climatology, but until recently they have been little used by biomedical researchers. We suggest that many of the ‘Big Data’ challenges facing the medical informatics community can be efficiently handled using national-scale cyberinfrastructure. Resources such as the Extreme Science and Discovery Environment, the Open Science Grid, and Internet2 provide economical and proven infrastructures for Big Data challenges, but these resources can be difficult to approach. Specialized web portals, support centers, and virtual organizations can be constructed on these resources to meet defined computational challenges, specifically for genomics. We provide examples of how this has been done in basic biology as an illustration for the biomedical informatics community.

De novo transcript sequence reconstruction from RNA-seq using the Trinity platform for reference generation and analysis

De novo assembly of RNA-seq data enables researchers to study transcriptomes without the need for a genome sequence; this approach can be usefully applied, for instance, in research on 'non-model organisms' of ecological and evolutionary importance, cancer samples or the microbiome. In this protocol we describe the use of the Trinity platform for de novo transcriptome assembly from RNA-seq data in non-model organisms. We also present Trinity-supported companion utilities for downstream applications, including RSEM for transcript abundance estimation, R/Bioconductor packages for identifying differentially expressed transcripts across samples and approaches to identify protein-coding genes. In the procedure, we provide a workflow for genome-independent transcriptome analysis leveraging the Trinity platform. The software, documentation and demonstrations are freely available from http://trinityrnaseq.sourceforge.net. The run time of this protocol is highly dependent on the size and complexity of data to be analyzed. The example data set analyzed in the procedure detailed herein can be processed in less than 5 h.

De novo transcript sequence reconstruction from RNA-seq using the Trinity platform for reference generation and analysis

De novo assembly of RNA-seq data enables researchers to study transcriptomes without the need for a genome sequence; this approach can be usefully applied, for instance, in research on 'non-model organisms' of ecological and evolutionary importance, cancer samples or the microbiome. In this protocol we describe the use of the Trinity platform for de novo transcriptome assembly from RNA-seq data in non-model organisms. We also present Trinity-supported companion utilities for downstream applications, including RSEM for transcript abundance estimation, R/Bioconductor packages for identifying differentially expressed transcripts across samples and approaches to identify protein-coding genes. In the procedure, we provide a workflow for genome-independent transcriptome analysis leveraging the Trinity platform. The software, documentation and demonstrations are freely available from http://trinityrnaseq.sourceforge.net. The run time of this protocol is highly dependent on the size and complexity of data to be analyzed. The example data set analyzed in the procedure detailed herein can be processed in less than 5 h.

De novo transcript sequence reconstruction from RNA-seq using the Trinity platform for reference generation and analysis

De novo assembly of RNA-seq data enables researchers to study transcriptomes without the need for a genome sequence; this approach can be usefully applied, for instance, in research on 'non-model organisms' of ecological and evolutionary importance, cancer samples or the microbiome. In this protocol we describe the use of the Trinity platform for de novo transcriptome assembly from RNA-seq data in non-model organisms. We also present Trinity-supported companion utilities for downstream applications, including RSEM for transcript abundance estimation, R/Bioconductor packages for identifying differentially expressed transcripts across samples and approaches to identify protein-coding genes. In the procedure, we provide a workflow for genome-independent transcriptome analysis leveraging the Trinity platform. The software, documentation and demonstrations are freely available from http://trinityrnaseq.sourceforge.net. The run time of this protocol is highly dependent on the size and complexity of data to be analyzed. The example data set analyzed in the procedure detailed herein can be processed in less than 5 h.

Probing the molecular-scale lipid bilayer response to shear flow using nonequilibrium molecular dynamics

A nonequilibrium molecular dynamics simulation of the response of dimyristoylphosphatidylcholine (DMPC) bilayers to a solvent shear flow is presented. Application of shear flow to planar, stationary DMPC bilayers results in a redistribution of the membrane density profile along the bilayer normal due to the alignment of the lipids in the direction of flow and an increase in average lipid chain length. An increase in the intermolecular and intramolecular order of the lipids in response to the shear flow is also observed. This study provides groundwork for understanding the mechanism of the full response of lipid bilayers to externally imposed solvent shear flows, beginning with the response in the absence of collective lipid motions such as undulations and bilayer flow.

Membrane remodeling from N-BAR domain interactions: insights from multi-scale simulation

Liposome remodeling processes (e.g., vesiculation and tubulation) due to N-BAR domain interactions with the lipid bilayer are explored with a multi-scale simulation approach. Results from atomistic-level molecular dynamics simulations of membrane binding to the concave face of N-BAR domains are used along with discretized mesoscopic field-theoretic simulations to examine how the spontaneous curvature fields generated by N-BAR domains result in membrane remodeling. It is found that tubulation can be generated by anisotropic N-BAR spontaneous curvature fields, whereas vesiculation is only observed with isotropic N-BAR spontaneous curvature fields at high density. The results of the multi-scale simulations provide insight into recent experimental observations.

Direct observation of Bin/amphiphysin/Rvs (BAR) domain-induced membrane curvature by means of molecular dynamics simulations

The process of membrane curvature generation by BAR (Bin/amphiphysin/Rvs) domains is thought to involve the plastering of the negatively charged cell membrane to the positively charged concave surface of the BAR domain. Recent work [Peter, B. J., et al. (2004) Science, 303,495-499; Masuda, M., et al. (2006) EMBO J. 25, 2889-2897; and Gallop, J. L., et al. (2006) EMBO J. 25, 2898-2910] has demonstrated the importance of the charged, crescent-shaped surface and the N-terminal amphipathic helices (present in N-BAR domains) for generating membrane curvature. These experiments suggest that curvature is generated by the synergistic action of the N-terminal helices embedding in the lipid bilayer and the charged crescent-shaped dimer acting to "scaffold" membrane curvature. Here, we present atomistic molecular dynamics simulations that directly show membrane binding to the concave face of N-BAR domains, resulting in the generation of local membrane curvature that matches the curvature presented by the BAR domain. These simulations provide direct molecular-scale evidence that BAR domains create curvature by acting as a scaffold, forcing the membrane to locally adopt the intrinsic shape of the BAR domain. We find that BAR domains bind strongly through the maximum curvature surface and, additionally, at an orientation that presents a lesser degree of curvature, thus enabling N-BAR domains to induce a range of local curvatures. Finally, we find that the N-terminal region may play a role in biasing the orientations of N-BAR domains on the membrane surface to those that favor binding to the concave face and subsequent membrane bending.