title: A fast and robust protocol for metataxonomic analysis using RNAseq data.
abstract: Metagenomics is a rapidly emerging field aimed to analyze microbial diversity and dynamics by studying the genomic content of the microbiota. Metataxonomics tools analyze high-throughput sequencing data, primarily from 16S rRNA gene sequencing and DNAseq, to identify microorganisms and viruses within a complex mixture. With the growing demand for analysis of the functional microbiome, metatranscriptome studies attract more interest. To make metatranscriptomic data sufficient for metataxonomics, new analytical workflows are needed to deal with sparse and taxonomically less informative sequencing data.
  
  
  
  We present a new protocol, IMSA+A, for accurate taxonomy classification based on metatranscriptome data of any read length that can efficiently and robustly identify bacteria, fungi, and viruses in the same sample. The new protocol improves accuracy by using a conservative reference database, employing a new counting scheme, and by assembling shotgun reads. Assembly also reduces analysis runtime. Simulated data were utilized to evaluate the protocol by permuting common experimental variables. When applied to the real metatranscriptome data for mouse intestines colonized by ASF, the protocol showed superior performance in detection of the microorganisms compared to the existing metataxonomics tools. IMSA+A is available at https://github.com/JeremyCoxBMI/IMSA-A .
  
  
  
  The developed protocol addresses the need for taxonomy classification from RNAseq data. Previously not utilized, i.e., unmapped to a reference genome, RNAseq reads can now be used to gather taxonomic information about the microbiota present in a biological sample without conducting additional sequencing. Any metatranscriptome pipeline that includes assembly of reads can add this analysis with minimal additional cost of compute time. The new protocol also creates an opportunity to revisit old metatranscriptome data, where taxonomic content may be important but was not analyzed.
authors.affiliation: Department of Electrical Engineering and Computing Systems, University of Cincinnati, 2901 Woodside Drive, Cincinnati, OH, 45221, USA.|The Center for Autoimmune Genomics and Etiology, Cincinnati Children's Hospital Medical Center, 3333 Burnet Avenue, MLC 15012, Cincinnati, OH, 45229-3039, USA.
authors.forename: Jeremy W
authors.initials: JW
authors.lastname: Cox
authors.affiliation: The Center for Autoimmune Genomics and Etiology, Cincinnati Children's Hospital Medical Center, 3333 Burnet Avenue, MLC 15012, Cincinnati, OH, 45229-3039, USA.
authors.forename: Richard A
authors.initials: RA
authors.lastname: Ballweg
authors.affiliation: The Center for Autoimmune Genomics and Etiology, Cincinnati Children's Hospital Medical Center, 3333 Burnet Avenue, MLC 15012, Cincinnati, OH, 45229-3039, USA.
authors.forename: Diana H
authors.initials: DH
authors.lastname: Taft
authors.affiliation: Division of Biomedical Informatics, Cincinnati Children's Hospital Medical Center, 3333 Burnet Avenue, Cincinnati, OH, 45229, USA.
authors.forename: Prakash
authors.initials: P
authors.lastname: Velayutham
authors.affiliation: Division of Infectious Diseases, Cincinnati Children's Hospital Medical Center, 3333 Burnet Avenue, Cincinnati, OH, 45229, USA.
authors.forename: David B
authors.initials: DB
authors.lastname: Haslam
authors.affiliation: The Center for Autoimmune Genomics and Etiology, Cincinnati Children's Hospital Medical Center, 3333 Burnet Avenue, MLC 15012, Cincinnati, OH, 45229-3039, USA. Alexey.Porollo@cchmc.org.|Division of Biomedical Informatics, Cincinnati Children's Hospital Medical Center, 3333 Burnet Avenue, Cincinnati, OH, 45229, USA. Alexey.Porollo@cchmc.org.
authors.forename: Aleksey
authors.identifier: 0000-0002-3202-5099
authors.initials: A
authors.lastname: Porollo
mesh_terms: D000465:Algorithms; D000818:Animals; D001419:Bacteria / Q000145:classification* / Q000235:genetics; D001483:Base Sequence; D030541:Databases, Genetic; D005658:Fungi / Q000145:classification* / Q000235:genetics; D059014:High-Throughput Nucleotide Sequencing; D056186:Metagenomics / Q000379:methods*; D051379:Mice; D064307:Microbiota / Q000235:genetics*; D012336:RNA, Ribosomal, 16S / Q000235:genetics; D017423:Sequence Analysis, RNA; D014780:Viruses / Q000145:classification* / Q000235:genetics
chemical_list: D012336:RNA, Ribosomal, 16S
keywords: Altered Schaedler flora; Assembly of shotgun reads; Metagenome; Metataxonomics; Metatranscriptome; Microbiome; RNAseq