Draft Genome Sequence of the Free-Living, Iridescent Bacterium Tenacibaculum mesophilum Strain ECR.

Here, we report the genome sequence of Tenacibaculum mesophilum strain ECR, which was isolated from the river/ocean interface at Trunk River in Falmouth, Massachusetts. The isolation and sequencing were performed as part of the 2016 and 2018 Microbial Diversity courses at the Marine Biological Laboratory in Woods Hole, Massachusetts.

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

BACKGROUND: Whole-genome sequencing data from wild-caught individuals of closely related North American killifish species (Fundulus xenicus, Fundulus catenatus, Fundulus nottii, and Fundulus olivaceus) were obtained using long-read Oxford Nanopore Technology (ONT) PromethION and short-read Illumina platforms. FINDINGS: Draft de novo reference genome assemblies were generated using a combination of long and short sequencing reads. For each species, the PromethION platform was used to generate 30-45× sequence coverage, and the Illumina platform was used to generate 50-160× sequence coverage. Illumina-only assemblies were fragmented with high numbers of contigs, while ONT-only assemblies were error prone with low BUSCO scores. The highest N50 values, ranging from 0.4 to 2.7 Mb, were from assemblies generated using a combination of short- and long-read data. BUSCO scores were consistently >90% complete using the Eukaryota database. CONCLUSIONS: High-quality genomes can be obtained from a combination of using short-read Illumina data to polish assemblies generated with long-read ONT data. Draft assemblies and raw sequencing data are available for public use. We encourage use and reuse of these data for assembly benchmarking and other analyses.

Tximeta: Reference sequence checksums for provenance identification in RNA-seq.

Correct annotation metadata is critical for reproducible and accurate RNA-seq analysis. When files are shared publicly or among collaborators with incorrect or missing annotation metadata, it becomes difficult or impossible to reproduce bioinformatic analyses from raw data. It also makes it more difficult to locate the transcriptomic features, such as transcripts or genes, in their proper genomic context, which is necessary for overlapping expression data with other datasets. We provide a solution in the form of an R/Bioconductor package tximeta that performs numerous annotation and metadata gathering tasks automatically on behalf of users during the import of transcript quantification files. The correct reference transcriptome is identified via a hashed checksum stored in the quantification output, and key transcript databases are downloaded and cached locally. The computational paradigm of automatically adding annotation metadata based on reference sequence checksums can greatly facilitate genomic workflows, by helping to reduce overhead during bioinformatic analyses, preventing costly bioinformatic mistakes, and promoting computational reproducibility. The tximeta package is available at https://bioconductor.org/packages/tximeta.

Keeping it light: (re)analyzing community-wide datasets without major infrastructure.

DNA sequencing technology has revolutionized the field of biology, shifting biology from a data-limited to data-rich state. Central to the interpretation of sequencing data are the computational tools and approaches that convert raw data into biologically meaningful information. Both the tools and the generation of data are actively evolving, yet the practice of re-analysis of previously generated data with new tools is not commonplace. Re-analysis of existing data provides an affordable means of generating new information and will likely become more routine within biology, yet necessitates a new set of considerations for best practices and resource development. Here, we discuss several practices that we believe to be broadly applicable when re-analyzing data, especially when done by small research groups.

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

BACKGROUND: De novo transcriptome assemblies are required prior to analyzing RNA sequencing 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 as part of the Marine Microbial Eukaryotic Transcriptome Sequencing Project. 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. RESULTS: New 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. Assemblies from the Dinoflagellata showed a higher number of contigs and unique k-mers than transcriptomes from other phyla, while assemblies from Ciliophora had a lower percentage of open reading frames compared to other phyla. CONCLUSIONS: Given 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.

Patient satisfaction and the impact of written material about postpartum contraceptive decisions.

OBJECTIVE: The purpose of this study was to evaluate the impact of written educational material about patient satisfaction and decision-making regarding postpartum contraception. STUDY DESIGN: Baseline patient satisfaction and effectiveness of contraceptive counseling on a postpartum unit was evaluated with the use of a self-administered questionnaire. Data were compared with patients who received additional comprehensive written educational material during their postpartum hospitalization. RESULTS: A total of 109 women participated in the study (control subjects, 53; intervention group, 56). Demographics and patient satisfaction with contraceptive counseling were similar between groups. Thirty-four percent of the control subjects reported having received some sort of written information; all women in the intervention group received a standardized comprehensive booklet of information during their postpartum stay (P <.01). Among the women who received written information, the intervention group was more likely to state that written material contributed to their ultimate choice in birth control (P <.01). CONCLUSION: The postpartum distribution of written material about contraceptive options increases a woman's ability to make an informed decision regarding birth control.