MarkerMiner 1.0: A New Application for Phylogenetic Marker Development Using Angiosperm Transcriptomes
Premise of the study: Targeted sequencing using next-generation sequencing (NGS) platforms offers enormous potential for plant systematics by enabling economical acquisition of multilocus data sets that can resolve difficult phylogenetic problems. However, because discovery of single-copy nuclear (S...
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Published in | Applications in plant sciences Vol. 3; no. 4 |
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Main Authors | , , , , , , , , |
Format | Journal Article |
Language | English |
Published |
United States
Botanical Society of America
01.04.2015
John Wiley & Sons, Inc |
Subjects | |
Online Access | Get full text |
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Summary: | Premise of the study: Targeted sequencing using next-generation sequencing (NGS) platforms offers enormous potential for plant systematics by enabling economical acquisition of multilocus data sets that can resolve difficult phylogenetic problems. However, because discovery of single-copy nuclear (SCN) loci from NGS data requires both bioinformatics skills and access to high-performance computing resources, the application of NGS data has been limited. Methods and Results: We developed MarkerMiner 1.0, a fully automated, open-access bioinformatic workflow and application for discovery of SCN loci in angiosperms. Our new tool identified as many as 1993 SCN loci from transcriptomic data sampled as part of four independent test cases representing marker development projects at different phylogenetic scales. Conclusions: MarkerMiner is an easy-to-use and effective tool for discovery of putative SCN loci. It can be run locally or via the Web, and its tabular and alignment outputs facilitate efficient downstream assessments of phylogenetic utility, locus selection, intron-exon boundary prediction, and primer or probe development. |
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Bibliography: | http://dx.doi.org/10.3732%2Fapps.1400115 The authors thank all oneKP contributors, especially Gane Ka‐Shu Wong, and BGI. Funding for S.C. was provided by the National Science Foundation (NSF; grant IOS‐0922742 [P.S.S., D.E.S., W.B.B.]). Research funding for N.G. and G.T.G. was provided in part by NSF Doctoral Dissertation Improvement grants DEB‐1310839 (P.S.S. and N.G.) and DEB‐1210671 (P.S.S. and G.T.G.), respectively. The salary of I.J.T. was provided by the David Burpee Endowment and Chris Martine (Bucknell University). Authors are listed alphabetically by surname and contributed equally. ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 content type line 23 The authors thank all oneKP contributors, especially Gane Ka-Shu Wong, and BGI. Funding for S.C. was provided by the National Science Foundation (NSF; grant IOS-0922742 [P.S.S., D.E.S., W.B.B.]). Research funding for N.G. and G.T.G. was provided in part by NSF Doctoral Dissertation Improvement grants DEB-1310839 (P.S.S. and N.G.) and DEB-1210671 (P.S.S. and G.T.G.), respectively. The salary of I.J.T. was provided by the David Burpee Endowment and Chris Martine (Bucknell University). |
ISSN: | 2168-0450 2168-0450 |
DOI: | 10.3732/apps.1400115 |