GenBank as a source to monitor and analyze Host-Microbiome data

Author:

Ramanan Vivek12,Mechery Shanti2,Sarkar Indra Neil123ORCID

Affiliation:

1. Center of Computational Molecular Biology Brown University , Providence, RI, USA

2. Center for Biomedical Informatics Brown University , Providence, RI, USA

3. Rhode Island Quality Institute , Providence, RI, USA

Abstract

Abstract Motivation Microbiome datasets are often constrained by sequencing limitations. GenBank is the largest collection of publicly available DNA sequences, which is maintained by the National Center of Biotechnology Information (NCBI). The metadata of GenBank records are a largely understudied resource and may be uniquely leveraged to access the sum of prior studies focused on microbiome composition. Here, we developed a computational pipeline to analyze GenBank metadata, containing data on hosts, microorganisms and their place of origin. This work provides the first opportunity to leverage the totality of GenBank to shed light on compositional data practices that shape how microbiome datasets are formed as well as examine host–microbiome relationships. Results The collected dataset contains multiple kingdoms of microorganisms, consisting of bacteria, viruses, archaea, protozoa, fungi, and invertebrate parasites, and hosts of multiple taxonomical classes, including mammals, birds and fish. A human data subset of this dataset provides insights to gaps in current microbiome data collection, which is biased towards clinically relevant pathogens. Clustering and phylogenic analysis reveals the potential to use these data to model host taxonomy and evolution, revealing groupings formed by host diet, environment and coevolution. Availability and implementation GenBank Host-Microbiome Pipeline is available at https://github.com/bcbi/genbank_holobiome. The GenBank loader is available at https://github.com/bcbi/genbank_loader. Supplementary information Supplementary data are available at Bioinformatics online.

Funder

National Institutes of Health

Publisher

Oxford University Press (OUP)

Subject

Computational Mathematics,Computational Theory and Mathematics,Computer Science Applications,Molecular Biology,Biochemistry,Statistics and Probability

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