title: Ghost-tree: creating hybrid-gene phylogenetic trees for diversity analyses.
abstract: BACKGROUND
  Fungi play critical roles in many ecosystems, cause serious diseases in plants and animals, and pose significant threats to human health and structural integrity problems in built environments. While most fungal diversity remains unknown, the development of PCR primers for the internal transcribed spacer (ITS) combined with next-generation sequencing has substantially improved our ability to profile fungal microbial diversity. Although the high sequence variability in the ITS region facilitates more accurate species identification, it also makes multiple sequence alignment and phylogenetic analysis unreliable across evolutionarily distant fungi because the sequences are hard to align accurately. To address this issue, we created ghost-tree, a bioinformatics tool that integrates sequence data from two genetic markers into a single phylogenetic tree that can be used for diversity analyses. Our approach starts with a "foundation" phylogeny based on one genetic marker whose sequences can be aligned across organisms spanning divergent taxonomic groups (e.g., fungal families). Then, "extension" phylogenies are built for more closely related organisms (e.g., fungal species or strains) using a second more rapidly evolving genetic marker. These smaller phylogenies are then grafted onto the foundation tree by mapping taxonomic names such that each corresponding foundation-tree tip would branch into its new "extension tree" child.
  
  
  RESULTS
  We applied ghost-tree to graft fungal extension phylogenies derived from ITS sequences onto a foundation phylogeny derived from fungal 18S sequences. Our analysis of simulated and real fungal ITS data sets found that phylogenetic distances between fungal communities computed using ghost-tree phylogenies explained significantly more variance than non-phylogenetic distances. The phylogenetic metrics also improved our ability to distinguish small differences (effect sizes) between microbial communities, though results were similar to non-phylogenetic methods for larger effect sizes.
  
  
  CONCLUSIONS
  The Silva/UNITE-based ghost tree presented here can be easily integrated into existing fungal analysis pipelines to enhance the resolution of fungal community differences and improve understanding of these communities in built environments. The ghost-tree software package can also be used to develop phylogenetic trees for other marker gene sets that afford different taxonomic resolution, or for bridging genome trees with amplicon trees.
  
  
  BACKGROUND
  ghost-tree is pip-installable. All source code, documentation, and test code are available under the BSD license at https://github.com/JTFouquier/ghost-tree .
authors.affiliation: Graduate Program in Bioinformatics and Medical Informatics, San Diego State University, San Diego, CA, USA. jennietf@gmail.com.
authors.forename: Jennifer
authors.initials: J
authors.lastname: Fouquier
authors.affiliation: Center for Microbial Genetics and Genomics, Northern Arizona University, Flagstaff, AZ, USA. jai.rideout@gmail.com.
authors.forename: Jai Ram
authors.initials: JR
authors.lastname: Rideout
authors.affiliation: Center for Microbial Genetics and Genomics, Northern Arizona University, Flagstaff, AZ, USA. ebolyen@gmail.com.
authors.forename: Evan
authors.initials: E
authors.lastname: Bolyen
authors.affiliation: Center for Microbial Genetics and Genomics, Northern Arizona University, Flagstaff, AZ, USA. chasejohnh@gmail.com.
authors.forename: John
authors.initials: J
authors.lastname: Chase
authors.affiliation: Center for Microbial Genetics and Genomics, Northern Arizona University, Flagstaff, AZ, USA. shiffy35@gmail.com.|Department of Biological Sciences, Northern Arizona University, Flagstaff, AZ, USA. shiffy35@gmail.com.
authors.forename: Arron
authors.initials: A
authors.lastname: Shiffer
authors.affiliation: Institute for Systems Biology, Seattle, WA, USA. wasade@gmail.com.
authors.forename: Daniel
authors.initials: D
authors.lastname: McDonald
authors.affiliation: Department of Pediatrics, and Department of Computer Science and Engineering, University of California San Diego, San Diego, CA, USA. robknight@ucsd.edu.
authors.forename: Rob
authors.initials: R
authors.lastname: Knight
authors.affiliation: Center for Microbial Genetics and Genomics, Northern Arizona University, Flagstaff, AZ, USA. greg.caporaso@gmail.com.|Department of Biological Sciences, Northern Arizona University, Flagstaff, AZ, USA. greg.caporaso@gmail.com.
authors.forename: J Gregory
authors.initials: JG
authors.lastname: Caporaso
authors.affiliation: Graduate Program in Bioinformatics and Medical Informatics, San Diego State University, San Diego, CA, USA. skelley@mail.sdsu.edu.|Department of Biology, San Diego State University, San Diego, CA, USA. skelley@mail.sdsu.edu.|San Diego State University, 5500 Campanile Drive, San Diego, CA, 92182-4614, USA. skelley@mail.sdsu.edu.
authors.forename: Scott T
authors.initials: ST
authors.lastname: Kelley
mesh_terms: D019295:Computational Biology; D021901:DNA, Intergenic / Q000235:genetics*; D019143:Evolution, Molecular; D005658:Fungi / Q000145:classification / Q000235:genetics*; D059014:High-Throughput Nucleotide Sequencing; D006801:Humans; D064307:Microbiota / Q000235:genetics*; D050506:Mutant Chimeric Proteins / Q000235:genetics*; D010802:Phylogeny; D025341:Principal Component Analysis; D012463:Saliva / Q000382:microbiology*
chemical_list: D021901:DNA, Intergenic; D050506:Mutant Chimeric Proteins