Using phylogenetically-informed annotation (PIA) to search for light-interacting genes in transcriptomes from non-model organisms

Simple item page
dc.contributor.authorSpeiser, Daniel I.
dc.contributor.authorPankey, M. Sabrina
dc.contributor.authorZaharoff, Alexander K.
dc.contributor.authorBattelle, Barbara A.
dc.contributor.authorBracken-Grissom, Heather D.
dc.contributor.authorBreinholt, Jesse W.
dc.contributor.authorBybee, Seth M.
dc.contributor.authorCronin, Thomas W.
dc.contributor.authorGarm, Anders
dc.contributor.authorLindgren, Annie R.
dc.contributor.authorPatel, Nipam H.
dc.contributor.authorPorter, Megan L.
dc.contributor.authorProtas, Meredith E.
dc.contributor.authorRivera, Ajna S.
dc.contributor.authorSerb, Jeanne M.
dc.contributor.authorZigler, Kirk S.
dc.contributor.authorCrandall, Keith A.
dc.contributor.authorOakley, Todd H.
dc.date.accessioned2019-04-10T15:33:28Z
dc.date.available2019-04-10T15:33:28Z
dc.date.issued2014-11-19
dc.description.abstractBackground: Tools for high throughput sequencing and de novo assembly make the analysis of transcriptomes (i.e. the suite of genes expressed in a tissue) feasible for almost any organism. Yet a challenge for biologists is that it can be difficult to assign identities to gene sequences, especially from non-model organisms. Phylogenetic analyses are one useful method for assigning identities to these sequences, but such methods tend to be time-consuming because of the need to re-calculate trees for every gene of interest and each time a new data set is analyzed. In response, we employed existing tools for phylogenetic analysis to produce a computationally efficient, tree-based approach for annotating transcriptomes or new genomes that we term Phylogenetically-Informed Annotation (PIA), which places uncharacterized genes into pre-calculated phylogenies of gene families. Results: We generated maximum likelihood trees for 109 genes from a Light Interaction Toolkit (LIT), a collection of genes that underlie the function or development of light-interacting structures in metazoans. To do so, we searched protein sequences predicted from 29 fully-sequenced genomes and built trees using tools for phylogenetic analysis in the Osiris package of Galaxy (an open-source workflow management system). Next, to rapidly annotate transcriptomes from organisms that lack sequenced genomes, we repurposed a maximum likelihood-based Evolutionary Placement Algorithm (implemented in RAxML) to place sequences of potential LIT genes on to our pre-calculated gene trees. Finally, we implemented PIA in Galaxy and used it to search for LIT genes in 28 newly-sequenced transcriptomes from the light-interacting tissues of a range of cephalopod mollusks, arthropods, and cubozoan cnidarians. Our new trees for LIT genes are available on the Bitbucket public repository (http://bitbucket.org/osiris_phylogenetics/pia/) and we demonstrate PIA on a publicly-accessible web server (http://galaxy-dev.cnsi.ucsb.edu/pia/). Conclusions: Our new trees for LIT genes will be a valuable resource for researchers studying the evolution of eyes or other light-interacting structures. We also introduce PIA, a high throughput method for using phylogenetic relationships to identify LIT genes in transcriptomes from non-model organisms. With simple modifications, our methods may be used to search for different sets of genes or to annotate data sets from taxa outside of Metazoa.en_US
dc.description.sponsorshipWe acknowledge support from the Center for Scientific Computing at the CNSI and MRL: an NSF MRSEC (DMR-1121053) and NSF CNS-0960316. This work was funded by NSF EAGER-1045257 to THO. We thank Paul Weakliem and the Life Sciences Computing Group (LSCG) for extensive technical assistance. Also, thanks to THO’s Macroevolution honors’ students, in particular Jacquie Spring and Elmar Aliyev.en_US
dc.description.urihttps://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-014-0350-xen_US
dc.format.extent12 pagesen_US
dc.genrejournal articlesen_US
dc.identifierdoi:10.13016/m2soi1-m0j5
dc.identifier.citationDaniel I Speiser, M Sabrina Pankey, Alexander K Zaharoff, Barbara A Battelle, et.al, Using phylogenetically-informed annotation (PIA) to search for light-interacting genes in transcriptomes from non-model organisms, BMC Bioinformatics, 2014,15:350, https://doi.org/10.1186/s12859-014-0350-xen_US
dc.identifier.urihttps://doi.org/10.1186/s12859-014-0350-x
dc.identifier.urihttp://hdl.handle.net/11603/13386
dc.language.isoen_USen_US
dc.publisherBioMed Central Ltden_US
dc.relation.isAvailableAtThe University of Maryland, Baltimore County (UMBC)
dc.relation.ispartofUMBC Biological Sciences Department Collection
dc.relation.ispartofUMBC Faculty Collection
dc.rightsThis item is likely protected under Title 17 of the U.S. Copyright Law. Unless on a Creative Commons license, for uses protected by Copyright Law, contact the copyright holder or the author.
dc.rightsAttribution 4.0 International (CC BY 4.0)*
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/*
dc.subjectbioinformaticsen_US
dc.subjecteyesen_US
dc.subjectevolutionen_US
dc.subjectgalaxyen_US
dc.subjectnext- generation sequence analysisen_US
dc.subjectorthologyen_US
dc.subjectphototransductionen_US
dc.subjecttranscriptomesen_US
dc.subjectvisionen_US
dc.titleUsing phylogenetically-informed annotation (PIA) to search for light-interacting genes in transcriptomes from non-model organismsen_US
dc.typeTexten_US

Files

Original bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
s12859-014-0350-x.pdf
Size:
826.19 KB
Format:
Adobe Portable Document Format
Description:
Download
License bundle
Now showing 1 - 1 of 1
No Thumbnail Available
Name:
license.txt
Size:
2.56 KB
Format:
Item-specific license agreed upon to submission
Description:
Download

Collections

UMBC Biological Sciences Department
UMBC Faculty Collection