TagSeq for gene expression in non‐model plants: A pilot study at the Santa Rita Experimental Range NEON core site
AffiliationUniv Arizona, Dept Ecol & Evolutionary Biol
National Ecological Observatory Network (NEON)
MetadataShow full item record
CitationMarx, H. E., Scheidt, S., Barker, M. S., & Dlugosch, K. M. (2020). TagSeq for gene expression in non‐model plants: A pilot study at the Santa Rita Experimental Range NEON core site. Applications in Plant Sciences, 8(11), e11398.
JournalAPPLICATIONS IN PLANT SCIENCES
Rights© 2020 Marx et al. Applications in Plant Sciences published by Wiley Periodicals LLC on behalf of Botanical Society of America. This is an open access article under the terms of the Creative Commons Attribution License.
Collection InformationThis item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at firstname.lastname@example.org.
AbstractPremise TagSeq is a cost-effective approach for gene expression studies requiring a large number of samples. To date, TagSeq studies in plants have been limited to those with a high-quality reference genome. We tested the suitability of reference transcriptomes for TagSeq in non-model plants, as part of a study of natural gene expression variation at the Santa Rita Experimental Range National Ecological Observatory Network (NEON) core site. Methods Tissue for TagSeq was sampled from multiple individuals of four species (Bouteloua aristidoides and Eragrostis lehmanniana [Poaceae], Tidestromia lanuginosa [Amaranthaceae], and Parkinsonia florida [Fabaceae]) at two locations on three dates (56 samples total). One sample per species was used to create a reference transcriptome via standard RNA-seq. TagSeq performance was assessed by recovery of reference loci, specificity of tag alignments, and variation among samples. Results A high fraction of tags aligned to each reference and mapped uniquely. Expression patterns were quantifiable for tens of thousands of loci, which revealed consistent spatial differentiation in expression for all species. Discussion TagSeq using de novo reference transcriptomes was an effective approach to quantifying gene expression in this study. Tags were highly locus specific and generated biologically informative profiles for four non-model plant species.
NoteOpen access journal
VersionFinal published version
SponsorsNational Science Foundation
Except where otherwise noted, this item's license is described as © 2020 Marx et al. Applications in Plant Sciences published by Wiley Periodicals LLC on behalf of Botanical Society of America. This is an open access article under the terms of the Creative Commons Attribution License.