Comprehensive Analysis of Non Redundant Protein Database

Background: Scientists around the world use NCBI’s non-redundant (NR) database to identify the taxonomic origin and functional annotation of their favorite protein sequences using BLAST. Unfortunately, due to the exponential growth of this database, many scientists do not have a good understanding of the contents of the NR database. There is a need for tools to explore the contents of large biological datasets, such as NR, to better understand the assumptions and limitations of the data they contain. Results: Protein sequence data, protein functional annotation, and taxonomic assignment from NCBI’s NR database were placed into a BoaG database, a domain-specific language and shared data science infrastructure for genomics, along with a CD-HIT clustering of all these protein sequences at different sequence similarity levels. We show that BoaG can efficiently perform queries on this large dataset to determine the average length of protein sequences and identify the most common taxonomic assignments and functional annotations. Using the clustering information, we also show that the non-redundant (NR) database has a considerable amount of annotation redundancy at the 95% similarity level. Conclusions: We implemented BoaG and provided a web-based interface to BoaG’s infrastructure that will help researchers to explore the dataset further. Researchers can submit queries and download the results or share them with others. Availability and implementation: The web-interface of the BoaG infrastructure can be accessed here: http://boa.cs.iastate.edu/boag. Please use user = boag and password = boag to login. Source code and other documentation are also provided as a GitHub repository: https://github.com/boalang/NR_Dataset

Microbiome analyses of pacific white shrimp (Litopenaeus vannamei) collected from disparate geographical locations

In this study, the tail muscle microbiota of pacific white shrimp (Litopenaeus vannamei) sourced from five countries across Central and South America and Southeast Asia were determined and compared. The genomic DNA was sequenced at around 10 × coverage for each geographical location and was assembled de novo for comparative analysis. The assembled sequences for all the lines were classified based on their similarity to the sequences in the public database. We found that there is high correlation among the microbiota of shrimp from disparate regions, as well as the presence of some DNA from bacteria known to cause food poisoning in humans. Sequencing data has been deposited at NCBI-SRA database and can be found under the BioProject ID PRJNA282154